{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-15T03:24:29.859267Z",
     "start_time": "2020-02-15T03:24:27.252431Z"
    }
   },
   "outputs": [],
   "source": [
    "import importlib\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import plotly.graph_objects as go\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from scipy import signal\n",
    "from sklearn.ensemble import ExtraTreesClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "from hrvanalysis import get_time_domain_features, get_csi_cvi_features\n",
    "import librosa\n",
    "import librosa.display\n",
    "\n",
    "import feature_extractor\n",
    "import model_evaluation\n",
    "import util"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Explore data\n",
    "- Record indicating difficulty in high accuracy: b02 hour 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-15T03:24:32.872658Z",
     "start_time": "2020-02-15T03:24:31.756460Z"
    }
   },
   "outputs": [
    {
     "data": {
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RO6ylbnckHz3V1yPHzug7L9qhp164XZJ0z0H+cCMArKZOE8lm9g8lfULSEyWZpFLS0ZZd3impkrRD0j/okicAYH06dqavonKjz8fbNFc/Y3gSd+8/IUm65rsukCTduwZ+NPi/Nr4rerTFDiaSAQAbwJFhPx1ObO7xdyRP+QdzD5w4q91b5zSXZ9o7fM7ykSnTiDnn9PZP36WPfuVhfeCmlfmja4dOLkz9hwWX4sjw0RYh/8fpji3x7y9868Bg7HTVcAL2yecPJ2IPrNyYKny0mTffy7R5LtPxDmOlbz52XJL01At36LLztkqS/n/2zju8rfJ8w/eRZUke8t6xM5y99x5AwggQ9p6FAmXT0kHbHxQoZdNSyl4tEEgCIYyEACEhe+8dO47jEdvxHrJlben8/pCPYlvDkizHJjn3demKI0vnfLJlne97vud93hLZ3S4jIyNzWglYSBYEIQn4DAgDGoG7gDjgTm/PEUWxBqcjGeD8wIcpIyMjI/NLpUbvXCgmtsvHC8SJcrzKuciZOTAZpULoEY7kRi8ZyXK0hYyMjIzMmYCnprLS5qkU7+Qvzqa7znmANB8ItOlueyobza6vu6J5X63ezPQX1zDz5bWuzeOupsFg9RhtAZ13JEub8H0SogDon+z8t6C6K4VkcxsjgYQz9znw11NW73RPZyVEktkiJJ/oAXNCGRkZmbOJYBzJD+N0FluA80VR/EgURX8+vbfhdC+PDeKcMjIyMjK/UGr17h27YyLCA1qUHa/WkxilIilaTa/4CIp7gPuk0WhFEJwO5NY4oy3s3TQqGRkZGRmZ0CBt+LbeMNWEK1AqhIBFwFq9xTUPkHom1OjNvp7SIUcrm1xfd4Urde3RaoxWO+U6E9uO14b8+J5wRlu0dfB2JgqiNcW1BuIiw4ltEaqTtWqi1UoKWqq+uoJafdtoMwmtRhmUw7qswSkkZ8RpiFCFkaxVd8kmgoyMjIyMd4IRki8GROALURR3B/C8Yy3/ZgdxThkZGRmZXyiS46gzjuSyBiOZCU7nSUZsBJW6HtBsz2RDq1aiaJX7BxCtDpMdyTIyMjIyv3gksVhyxAIIghDwZjC0OFO1LUKy5EjWd86RfLSiEYBJ/RIoqQ99zu+a3EpiI8IJUwjsK2kI+fHbY7TYMdscbhnJMSEUkvu0zKXA+bvMjI+grKHr5lS+HcmBv55ynZG4yHAiVc73pNy4UUZGRub0E4yQ3L/l37UBPq+x5d+YIM4pIyMjI/MLRXIkSw4kcC6KAlmEVuhMpMU4n58QrQq4yU9XoDNaXa6e1kSrwzFa7ac1U1FGRkZGRibUSNfp9hFOgW4GA1TrzSRJ0RZRwTXsa09JnZHYiHBG9YqltN6AKHa+eV9rDpbpmDkwiaHp2tMiJDcYnT+PeDdHcoiiLeqa6Z0Y1ea+tFgNFY1d02zPYLFhsNg9CskxGmVQr6e8wUR6bITr/04hvOuaBcrIyMjIuBOMkCxdfZp8Psodafuz+21kMjIyMjKnjWq9BUGgTeafVuNsSOfws2N7ZaOJ1BgN4FyAdjZXMRQ0Gq1tciMlotRhADRb5HgLGRkZGZlfLpJY3NqRDC2bwQE0zDXb7DSZbC5BMS5ShUI4tdEcLNVNZlK0arISIjFZHVR38nitMVntlNYbGZASzcheseSUN3b8pE5S39zS3NCDcA+dcyQ7HCLlDSYy4yPa3J8eq6Gii6q8aj30yJDQapQBvYckTupMZMRqXP9P0aqpajSHfBNBRkZGRsY7wQjJUkBUWoDPG9ryb3UQ55SRkZGR+YVSqzcTH6lCGXbqkhOjCUcUodnS8aLIaLHTaLK5hOSEKBU6oxVrNzt+dV6E5OiWzGQ53kJGRkZG5peM1AsgWtVWSA7UkXxKUHQKyWEKgfhIFTWd3BSu1ptJ1qpJbonM6GxURmsKa5oRReifHE1mfCT1BisGP+YsnaHB4Bx/+4zkKJUSQeicI7mm2YzNIZLeSoQFSI+NoEZvwWwL/eZ3VZNT2Jd+P63RqoOPtkiPay0kazDbHEHlLcvIyMjIBEcwQvLhln/n+PsEQRAE4Bqc2co7gzinjIyMjMwvFGeDHW9lmh1P/CsanU6ZtFaOZID6bnYlN5qsru71rYmShWQZGRkZmTOARpONaA+9AAKNp6pvEUgTok5dMxOiVCFxJCdr1a5MYek8oaCguhmA7OQoesU5XbwnuzhCod7g/JnGR7WdWygUAtHq4JrTSUiuY2lTXiKtRViuagydm1uiukVITvEkJAcRj2Ky2mkwWEnVnnoNkkgtnUtGRkZGpusJRkj+HhCAeYIgjPPzOY8CA1u+XhbEOWVkZGRkfqHUNpvb5CPDqQ7k/ixEKxvbLn4SWo7V3fEWjUYbMRFKt/ujJZFcFpJlZGRkZH7BNJlsHitvAhUBdUb3rOW4yHDX/cEgiiJVTSZStGoSWjaYGwydyxBuTWGNHoDspGh6tcRBlHZBQ7/WeMtIBqd435loC0lITotp70h2/r8rRPLqJuc5PTqSNc5+EoFUl0nzvqRWx5NE6qomOT1TRkZG5nQRjJD8IVAFhAHLBUGY5u2BgiBECILwD+BlnG7kAuCLYAba6phhgiCMEAThDkEQ3hAEYasgCAZBEMSW29OdOb6H8/UWBOFeQRAWCIJwSBCERkEQLIIgVAuCsEkQhGcEQegdynPKyMjInEnU6i1u+XiBOJJPCcltu713d8M9ndGzI/l0RFtU6Ews2F6MxSY39JORkZGR6RoaTVa3fGRwCsKB5NtKj42LODUXiI0IR2cM/jqpN9swWR0ka9Uu4TWUjuTKRjNxkeFEqMJaOZK7VqyUhHBPcwttkM3pJKS5lHu0hfP/UvVXKKluMqMQcDMTwKl5oD4AcbxGispo1bwvJUZ2JMvIyMicbtxnBh0gimKzIAh34nQWpwIbBUHYAdRJjxEE4W/AcOBCIBang9kM3CKKYmdXvYuBqzt5DL8QBOFb4HKc429PUsttOvCYIAhPiKL4z9MxLhkZGZlfEtV6syuOQkJyJfmzKKppyTyUmvRIx+pOR7LF5sBotXtutqfqWiHZancw+1/rMFjshIcpuH5CVpecR0ZGRkbm7KbJ5LkXgFajpNlix2Z3tOl/4A2XQNqq6W5MRDg55YH2bj9Fdav8XVe0RQjnBTV6s2vekaJVE6YQKGswhOz4nqhvthARHoYmPMzte8FEQbSmotFEmEJw5VRLpMU6RfLyLmi4V9VkJjHa+bNrT2tDQXyUuwPbEzUtUSitHcnJ2q6L5pCRkZGR8UwwjmREUfwRuBFowimyTgLm4nQdAzwNXAfEtXy/AbhCFMUdnRwvOJ3QrakDjoXguJ4YwSkReSdOZ/XdwPXA74HNLd9TA68IgvB4F43jF0VVk4lnlx9h1ZHK7h6KjIxMN2OyOju1p7QrpQzEkVzXbCZMIbgcOlIJa10Iu7MHihTJEePDkaw3h75xDcCe4noMFuexlx8o75JzyMjIyMjINJlsnh3JLeKy3s8NU53LkXzqmul0JAfvsJWE5KRoNWplGJGqMFfGcChwCsnO+YYyTEGqVt0lYmtr6g1W4iPd5xXgjIJoMgf/+sp1Jpcg3ppotRKtWumKvggl1U3mNu7h1gQScSbhEpJbVbnFaJSolAqqu3FOKCMjI3O2EZSQDCCK4lc4hdY3gXqcgmv7WyPwDjBSFMWVnR6tkx3AiziF6mxRFBOB50N07PaYgLeAIaIoThJF8c+iKP5XFMUvRVH8tyiKM3DmP0s8LQjCoC4ayy+G//v6IB9uKuRPS/Z3eXdjGRmZno006W+/kJAWpv6UxtY1W4iPDHc1+5EE5c6UxFY3mXnlp9ygN7ykcXuMtnCVa4ZuQduaDceqCVMI3Dgxi63Ha7AFkC8oIyMjIyPjL40mq8cN00A2gwEajFaUCoFI1Sk/UIwmHL3ZFvQ1TBKhpViL+EhVSKMtnI38Tm2CJ0SrujxSq8FgIdZDPjJ03pFc2Whya7QnkR6noVzXBRnJerPHfGRwCsDg/3sI2m4eSAiCQIpWTVUXRHPIyMjIyHgmaCEZQBTFUlEUHxFFMQkYCVwG3ApcCUwEEkRRfFAUxbLOD9V1zudFUfyrKIpLRFEsDNVxvTBTFMWHRFE86mM8rwFftfxXCdzSxWPq0ZQ1GFmdW8Wkfgk0GKyyW05G5iyndelpa2JcTpSOFxC1eovLhQxOZ1CkKqxTWYH/3VTIW2uP89KK3KCeL43bU7O9KLVzodxs6RpH8q6iekb2imV8n3isdrHLm//IyMjIyJydeHUkuzZ0/bsOSz0FBOGUGzbWFXEVnDjqug63zCfiIsND2myvRm9p43xNiFJ3uZBcZ7C4RYFJdDraQmdyy0eWSIuN6BJHclWj2dUMrz2SIzmQuVyN3oJWrXSL/kjRqqmSM5JlZGRkThudEpJbI4riYVEUvxdFcaEoistEUdwdgjzkbkUUxXo/H/plq69HdsVYfimsyalEFOHFq0cSHxnOjsK6jp8kIyNzxlLlRUhWKxWowhR+LYrqDW2FZHAuHAMph2zP0YpGAIpqmjHbAhd8dT4cyWplGOFhgt8lv4GSX6VnSJqW7OQoAAprmrvkPDIyMjIyZy+iKHoVkgN1JOuM1jb5yNC6uii4a3n763AoHclGix292dZm7pIYpaJW37VCcn2zxWtesFYTTpPJiiiKHr/fERU6H47kGA0nQywkOxwiNb4cyRFBOJL15jb5yBLJWrXcbE9GRuaMweEI7nP+dBIyIfksp3WniIhuG0UPYGtBLRmxGvolRTGhbwI7i2QhWUbmbMabI1kQBL87kNc2W9w6fsdEdM6Zk1epR6kQsDlEjlXqA36+FG3hqQkRQJRa2SXN9mr1ZmqbLQxIiaZfUjQAfnfk+wAAIABJREFUBbKQfNaTU97Iq6vy2FfS0N1DkZGROUMwWOzYHaLH61xMgPm2OoPVbeO1s0KydB2W4qRC6Ug+lcXbVkjuckdys29HstUuYrYF7tNqMllptthJ8+pI1lCjN2MJ4tjeaDBasTlEr0JyMI7kOr27sQAgRauRHckyMjK/eOwOkbs/2cWgJ37k481dHb7QOWQhOTSMaPV1cbeNopsRRZHtBXVMyU5EEAQm9o2nuNbgmozJyMicfVQ3mREEPE78tRqlX9EWdc3uCwdtJxzJTSYrZQ1GrhrbC4DDJ3UBH8OXIxmczWv0nRC6vZFf5RS9B6ZqiY8MJzYinMKawIVwmTOHY5VNXPPOFl5ffYzr39vK9oLaLj2fKIrM31rETe9v44UfctD5Idw0maz8Zv4upjy/moXbT3Tp+ILFaLFTWNPcqUoHmbOL49V6SusN3T2MLkParNX6EJIDcSTHtReSIzspJJusaNVKV/M4ybEbCqo99HdIiFZhtNoxdlFsldXuoNFkc2U+t0erDtzBK1HZkh+c5sWRnBarQRQJ6Zqtqsl5zhSt53O6emUE8HrqDRaPP58UrRqd0YrJ2jW/GxkZGZnTwWfbivk5pxKFQuC5H3Ioqeu5cwz3WqUAEAQhHJgEDAPiAc9XinaIovhMZ87bkxAEQQnc2equ77trLN1Nca2B2mYLE/omADA0PQaAY5X6Njv6MjIyZw/VejMJkSrCw9z3Lf1Z9NnsDhoMVg/RFkpqgiwxPV7tdPDOGZrC13vLOBHERVoSmzw1IYIWIbkLHMn51U7ReEBKNIIg0CcxkhN1ckby2cyz3+egVAis+N1M7vt0N3/9+iArfjcLlbJrvAJf7irlyaWH6ZsYyfbCWvaXNrDg7ikuMccTf/36IKtzq+ibGMkT3x5kWEYMY7LiumR8gXK8Ws/rq4/x48EKLHYHYQqBy0dn8PcrhnutODhTqGoykVehZ0zvOKLVnVoSnHV8sqWIp5YdRhWm4J1bxzFnaGp3DynknLrOecpI9r9hLjjF4v4tcUwSnXck29pcg2P83Jz2B0/VVJJTuM5goZcq9AWoUixHQpTnzx1J0G8fueEPFTrn6/HmSE6NcR6votFERlxoXpu3ijSJ8DAFmnBFQOJ/g8HKyF7uP5+UlvFXN5nJSogMYrQyXYXDIbKvtIG4iHCyk6O7ezgyMj0WURT5ZEsR43rH8Z8bxzLz5bV8d+AkD5w7oLuH5pGgZo2CIKiBx4EHgWBWAmeMkAz8ERjS8vVBzmIheX+ps6R2VGYs4BQ6APKrmpjaP7HbxiUjI9N9OLuee8/H68hZ09CywPTkSA42G1jq7N0rLpJUrZryIHIBdUYrqjAFai9iXZRaSbMl9ELyiToDqjAF6S2uotQYTY/erZbpWvKrmlifV82fLhrMkLQYnrh0GHfP38X3B09y1djMkJ/PYLHxwo85TO6XwKJ7prBkdymPfXWA7/af5MoWh397DpQ2sPxAOb87fyB3zejHua+s4511+bx324SQjy8QRFHks23FPLP8COFhCm6e3JuRvWLJKW/koy1FFNc2s/CeKW5Nnc4Ufj5SycOL9mK02kmL0fDZ3ZMYkKLt7mH9IiitN/DcDzlM6BNPbbOFp5YdZsbAJNTKM+u9Igl8nhzJ0QG6YxsMFrcKHmmjpjMZya3zm7UaJRabA7PN3unfhadoi4SWiK06vYVeIRJbW1PfLM13PM+ZTv3MA/95leucG87eHMmSa1iaH4WCqkbfQjJIhoIAHckeKtykc1TrZSH5dFLXbOFoRRP9U6I8Os/LdUbu/2wP+0oaUAjw3FUjuWlS724YqYxMz2dvSQMFNc28cu0oshIiGZMVx/cHynuskBywXUUQBBXwE04hOR4QArydMQiCcB7wj5b/2oB7O2owKAjCbwRB2CUIwq7q6uouH+Pp5GCpDrVSweA050IkLUZDtFrJsSq57FpG5mzFl5CsVXfsSG5ocei0XzjERATvPJKczElaFelxEZQ3BL5wkpxQrTvQtyZKrURvDn2JZWm9kV7xESha3J+pMXKn8rOZxbtKUSoErp+QBThd9v2To/hoc1HQDZl8sWR3KfUGK4/NHYxCIXDt+EwGpkTz7vrjXs/39trjxGiU3DWjH1pNONeOz2R1TpWr7DkQTFY7+VVNnW5CIooiz32fw9+WHmbmwGQ2PHYeT18+nGvGZ/LEvGG8edNY9pxo4N+r8jp1np7K8Wo9Dy3aw8DUaN64aSw2h4N7P90tl4X7yX83FeJwiLx+01ienDeM0nojq3OquntYIafRKEVbuPuOlGEKolRhfkXB2B0iTWYbsZHtN4Sdxw22eqfR1DZ3WRtg3IYvapqc84TE6FNjlja0a5u75por5S/He3Ukt/y8OhNt4SMj2fm40L02KR4kxaeQ7H+/C6PFjtnmIC7S/eeTHC0J4cGPv6saJJ+pLN5ZwpQXVnPTB9uY8vxqHl60l9yWRtYA6/Oqmff6JvKr9PzjyhFM7pfIM98doSLETR1lZM4U1h2tRiHABcOcFU5zhqRw+GSjay3c0wim7vFRYBZOUdgIfAD8CpgLnOfHbXanR90DEARhCPAlp1zd/yeK4taOnieK4vuiKE4QRXFCcnJyl47xdLO/tIFhGTGuEnZBEBiQEk1eZVMHz5SRkTlTqW4yt8kYbI1Wo3QtVL1R35K/2j5bMUYTTqMxuO7lUrllYpSa9FgNFUE4cBpNVo/lvhJatRJ9F2StltYZyIw/5YRK1Wqoa7Zgtp29ApDRYmfpvjJ2/UKau+4urmfeGxsZ949VPLX0UNDinSiK/HCwnJkDk1ybNYIgcMe0vhwo1bG3CxrvLd5VwoheMYzv44ywUigE7j2nP7kVTaw76r45fqyyiRWHK7hjWl+XyHPVuF7YHGLAwltuRSOzXl7L+a9u4Ib3t3Yqp/TNNfl8uKmQX03tw4e3T3CL37p4ZDo3Tsziw02FnKg9sxz/DofIn5ccQK0M48PbJ3DZ6Axeu2Esx6ubeX31se4eXo/HZLXz5a5SLhudQUZcBLMGJZOsVbNs38nuHlrIcUVbeIl4iYnwL5O4yWRFFN17CkSqwlAIwQmj4IzVaBNtERF8hnB7qvUm4iPD28RyuaItuqjhnnRcTz0l4FRTwWA20SsaTcRGhHutsEiIVKFUCC7BORRUNZqJCA8jykdsTiD9Luqk6A8PGclJ2uBFflEU+b9vDjLm7ytZcag84OefjWw6VsNjXx1gcr8EPrpzIvfMzGZNTiVzX9vItBdWM/uf6/jV/3aQFK3m2wencduUPrx0zSgsdgfztxZ19/BPK/lVeh5cuIfXfs7r9Ca4zJnNxmPVjMqMI67lM25iP+dce1dRfXcOyyvBCMm3tPxbA4wRRfFeURQ/FUVxpSiK6/25hXD83YIgCP2AVYCU1/CaKIqvdOOQuh2r3cHBMh1js+Lb3J+dFHXGLcJkZGT8QxRFqvVmkmO8d+zuaBFaLzl03JxM4dgcIiZr4B3Ga/Rm4iLDUSkVpMdqONlgDFiQbjS6d6BvTZQ6jOYuciRnxp8q22ydC3g2YrbZufGDbfz2831c++5WXl6R291D8snRiiZu+XAbDQYrU7MTmb+tmIcW7g1qQyS3oonSeiMXDU9rc//V4zLRqpXM31IUolE7ya9q4lBZo1tkxuWjM8iI1fDOuuNuz3lvQwER4WHcMb2f677BqVoy4yNYnVPp97lNVjv3f7YHQYBHZg9gZ1E9L/8U3O96Q141/1qVx1Vje/HUZcNd7v72PHrBIMIUAm+tzQ/qPD2Vj7cUsau4nifnDSOlpcx9xsAkrh2fyfsbCsgpb+zgCGc3P+dUojfbuG688+8gTCFwyYg01uVVnXEbepIgG+PBkQz+bQbDqeiK9hvCgiAQrVYG3SCvyWRrI3Jr1ZIjufObuDVNFrcNpoToLhaSDb6FZOn1BeOcrdCZSffiRgbnpmCKVh1SR/LJBiMZcb7bJ8UE4EiW5oNxHoTkxJY4kNogemfsOdHAwu0nsDlEHv/mEDZ74PPKUJNT3sjc1zYw/cU1rMn1/1p5OrDYHPz1mwNkJ0fx/m0TOG9wCn+9ZCib/zKbv1w8hCnZiQxK1fLEpUP59sHprsik3omRTB+QxNJ9J88aQVVntHLTB9v4/kA5r/18jCV7Srt7SDI9FJ3Byv6SBmYNOmU0HZMVR3iYwM7inmmUCUZI7g+IwOuiKJ511gVBELKANYC0knpXFMVHu3FIPYLc8iZMVgdje7eNzM6Mj6C80YTF1v0XZRkZmdNLo8mGxebw6kiOiVDSbLFj9zGhlDKS25cyuhr9BLFgrNGfckmnx0Zgtjkb+gVCo9HqsxFXlFpJc4jLJJvNNmqbLW0cyZIQFMrFHzgnvz8drujxAvV76wvYX9LA81eN5IYJWby97jhLdvfMibrDIfLHL/cTrVby9f3TeOuWcTxx6TB+zqnky12Bj1lyAM8emtLm/ii1kivH9uKHQxUhLYf7du9JFAJcNjq9zf0qpYK7Zmazo6iO3a0mu+U6I0v3lXHDxKw2woggCMweksKm/Bq/hbf5W4sorGnmX9eN4fcXDuamSVl8tq3YlfvpL7V6M79fvJ+BKdG8cPVIryIyOPPHb57Um6/2lPrMIW8wWLD2AOHBH45WNPHiilzmDEnh6nFtM60fv2QosRHh/OXrgz4/k892vt1bRlqMhsnZp3p/TB+QhMnqYH+JrhtHFno6aiobowmnydzxtVMSkj1tvmo14TQFG21hbFsZJEU/hCTaQm92E5K1aiXhYQK1XSQke9s4d51fE3xGckWjkVQv+cgSKTGaoCKHvFHWYKRXvO+8Yme0hX+vR5qnxXuItlApFcRolNTqA5+zfLf/JGqlgn9eN5raZgvbC7tXtDFa7Nz76W5q9GZUSgUPLdzLkZM9Z4Pvy90llNQZeXLeMCJUpxzucZEq7junP6/eMIZ3bxvP3TOz23wf4IrRGZQ1GDlQdmZ9VnrjrbX51OrNLHtoOqOz4nhnnfcYMJmzm035NThEmDUwyXWfJjyMIWkxPervvzXBCMlSd6OebfvpAgRByMApIvdtuet/wAPdNqAexN4Sp+V+XJ+2juTMhEhE0bkrLSMjc3bRUcduVwdyH4s+SQhrLyRLz/W3Y3z7cUkLRCkXMNCGe7oOHMnRaiV6iy2kE8ayls/R1o1kUrugQY7OYOWqtzdz76e7ufzNTSFdWIYSg8XGhxsLuHBYKjdP7s3zV49kSnYCTy09RFGQjRi7kuUHyzlYpuPxS4e6NgDunNaX8X3ieXVVXsAbrluO1zA4Veuxwc1Nk3pjsTn4Zm9ZSMbucIh8u6+M6QOSvJwvi/jI8Dau5P9uLMQhwl0z+rk9PhDhzWJz8MHGQqYPSGRGywT7gXMH4BCd7tpAePb7HHRGC6/fNNavJnr3ndMfhSDw3gZ3tzXA66uPMeaZVUx9YQ35VYHFeNkdIi/8kMO0F1Zz36e7u3zTRmew8siivcRolLx07Si3fPf4KBVPXjaM/SUNZ13psb/UNVtYd7SaK8ZkENZqE2JSvwQEAbYV1Hbj6EJPk8lGeJjgtamsv45kSQCM9SAAajXKoKItXLnLHjOSO+9Irta793cQBIGEKBV1Qbhe/aGu2YJWo2wTp9Ga6E5kJFfozF4b7UmkxqhDGm1R1mDssCmhs1eGn45kLz0zJJKi1a4eGIGwOreSWYOSmTcqnYjwMFYergj4GKFkwfZiTtQZeP3GsSy6ZwqxEeHc/r/tQYnkoUYURT7aXMSozFjOGRR4ROfsISkoBAKqSPqlYrTY+XzHCS4Zmc6ozDiun5BJYU0zR+XITxkPbDxWjVajZExWW1Pm4DQtOeU98z0TjJAsuZATfT7qDEMQhDScIrLUNnEBcI8obysBsPdEAylaNRntyqayWnaiS+tlITmUHD6pa9PQQObMRxRFVh6u4IudJzBYfhkNQToWkjt2FdcbrCgVgqtbueu56uCb9NS0WiAmBJl52Giy+cxIjlYrEUUwdCLHtT2SK7KtI9n5OkLZcO+d9ccprGnm9xcMorbZwms/98zio+X7y2k02bh7ZjbgLDF/9foxKMMU/PaLfT3KJSqKIu+tP87AlGiuGH3KCapQCDw0ewAVjSZ+OOh/NqPF5mBnUR1T+3ueig3LiGF0Ziyf7ygJyWbG9sI6SuuNbi5WiUiVkjun9+PnnCq25NeQX6Vn/tZirhiT0WbjQ2JKv0QEAbYe71h4+zmnkuomM3fPyHbdl5UQyZwhKSzZVeq3AL/leA3f7C3j3ln9GZoe49dz0mI1XD2uF4t3lboJvWtyK3l1VR4zByYBIg8t3BtQue5LK3J5b0MB/VOiWZdXxS0fbguJAFZSZ+DRL/Zx3j/XccVbm3lk0V6eXX6EeW9upLCmmdduGOvmtJS4fHQG5wxK5oUfcvl6Tyk6g5WCaj3bC2rPaENAXmUTv5m/i5ve3+azjPz7g+XYHCJXjGn7dxAXqWJoWoxf7+dgMFrs/P27w1z6+kZeXXX6cjYbjVa0Gu9NZWMi/Mu39RZtAbREWwR+HW/ykN+s7USGcHtqmtwdyQAJUeoucyTXNVtcOcyeCA9ToAlXBOzgttod1DabvTbak0iN0YSsEZrBYqOuXQWVJwJptlfvxVgg4RSSA5sL1erNlNQZmdg3Hk14GOP6xLGruPvySB0Okf9tKmRKdgLTBiSRFqvh4zsnoTNaeXnF0W4bl8TW47XkV+m5fWpfr58LvoiPUjGhTwI/n4HNSdvz3YGTNJps3DqlDwAXDktDEGDV4TNfRJcJnC3Ha5mSnYiy3UbikDQtNXpzj9hIak8wQvJ8nI32Lg3xWHosgiAkA6uBwS13fQH8ShTFnrNK7WIKa5rZkl/jVbTZe6Kesb3j3C4q0gSipF7OSQ4Vzy4/wqWvb2Luaxt5etlhuUSmFVVNJh5YsJu5r23gqaWH/C7rFkWRwyd17Cis65ExLFIjkN98ups/f3WQK9/a3KXdpY9VNvHYkv08vGgvuzsxoZacrF6jLfwQkhsMFuIiVW6fLdGd6PZeq7e4OrEnBtGFXRRFv6ItgJDGW0gbclmtSkXjI1UIAiFb2BosNuZvLeLy0Rk8MmcgV4/txVe7S10ltz2J7w6cpG9iJBP7nqqEyYiL4PmrRrK/pKFHNQ7bWVTP4ZON3Dm9n1ucwrmDkumdEMlXAWTnHT6pw2R1MLmlEYcnbp7cm6OVTWwNgUvyy90laNVK5g5P9/qYu2f2o39yFHd9sour3t5MpDqMv1w8xONjYyPDGZYew9aCmo7PvauEtBhNm9w4gJsm96a22cLPfjibimub+cPi/WTGR/DgeQM6fHxrfjMrG6vdwUebC1331Tdb+PNXBxmSpuXDX03g8UuHklvRxOpc/xbHeZVNfLixgJsm9ebTuybz319NJL9Kz3Pf5wQ0tvbkV+m54q3NrDxcwZA0LVq1kr0l9Xy8pYj4SBUL7pnscnV7QhAE/nPjGIb3iuH3i/cz+pmVzP7Xem54fxvTX1rD08sOn3GxFyV1Bq57dys7iuoobTDw64938aOXTZ1v95YxOFXL0HSt2/emZCey50S9380zRVH0SxC2O0R+/fFOPt5ShCA4XfAvBZkPHigdVd74KwI2+Iy2UAZ1HZec0G2a7bkcyZ277hosNpotdlcDt9YkRqmoC6Khmz/UGyxe3bYS0QE4eCWqmsyIIn4JyY0mW6camUqUtcxXOhaSwzFa7X5t/NY3S9EWnn9GidGqgIXk/aXOprSjM50uwPF9Esgpb+zSObYvdhTVcVJn4qZJvV33DU7Tcu34LJbtPxnyyLRAmb+1mPjIcOaN8j4X6Ig5Q1PIKW90Vdn1NBwOkUNlOnQBRt61Z8H2EwxIiXbN05K1agalaNnZjRsVMl3Dz0cquevjnSzbH1zT3ZI6AyfqDEzzYA4ZkuY0Phyt6Hmu5GCE5I+B3cClgiDcENrh9DwEQUgAfgaGtdz1NXCrKIpnVkcNL5htdu7/bDfn/XMdN3+4ndn/XEdeu5KMumYLRbUGxvaOd3t+eqyGMIVAaRcLySarnUe/2Mfov6/kD4v3h2xHvaex7mgVH24q5Lrxmdw6pTcfbynis23F3T2sHoEoivz+i/2sya0iIUrFgu0nuPqdLR06vAwWG/fM38Wlr2/i+ve2MvPlNSzdV9ajBPpl+0+yaEcJv5mVzbu3jg+J4OCNA6UNXPbmJn44WMHGY9Xc+P5W1h4Nzjkg/R16W7z4s+hrMFg9uk+igxRqbXYHTWYbcRHOhUgwjmSDxY7NIXYYbQHBCd3eKKkzoFYqSIo+tYgKUwjER6pCtlO9JrcKg8XODROzALhlch/MNodfYt3ppMFgYevxWuaOSHfbZLh0VDrXjc/krbX57OjmrEOJjzYXEhcZzlVj3R29giBw5ZgMNufX+B0jsq/Eufgd064vQWuuGNOLxCgV764vCG7QLejNNn48WMG80elueYetiVQpmX/XZGYNSmJ0ZhwL7p7sMQZDYmp2InuKG3wKbw0GCxuP1bhFCQDMGphMr7gIFu044XP8VU0mbnhvGyarnfduG+/zNXgiOzmaS0ak89HmIspaGnM+0bJR+a/rR6NWhnHZqAxStGq+8jOf+801+USqlDx2kdOfMH1AEvfMzObznSVszu9YXPeE1e7gvs92oxBg2cMzeOfW8Xx292Q2PjabY89dzLKHZjCxr/eNB4m4SBVL7pvG+7eN568XD+Ff141m/q8ncctk55yjKzdo1uZWccl/NjLh2Z/5y1cHQprx7Y2/LXU211r64HRWPXoOY7Li+OOX+8mv0rd5XH6Vnt3F9Vw5tpdHJ96U7ATMNofrb9MXh8p0zHl1PcOeWsHTyw77zAp/a20+WwtqeemaUXz30AxumJDFhxsLT0tVmrPyxvt1LkYTTqPR2uF8SYqg8nSsaD+a7noem+RIPlUZFN2JDOHW1DQ533eeNsETolRd12yv2UKCF5FUIiaATGGJipYs+Y6iLVK0UoVT59dQpS0iYYfRFgHEddQbLC051Z7li6TowN3i+0t0KAQY0SsWgPF94nGIsN+Pv+OuYOm+MiJVYVwwLLXN/VeN7YXRamfVke6bi5U1GFl5pIIbJ/X2KxrKG3OGOl/bmh42r5T429JDzHtjE+f/e33Qc+v8qib2lzRw48SsNteL8X3j2Vtcf8ZtyJ4p5JQ3cqI2MM0qr7KJez/bzercKh5ZtJctxwOfw0mGj2n93Tf6h7RsXOecCUKyKIpmYB6wD/hMEIQ3BEEYGvKRdTGCIHwsCILYcnvay2NigZXAqJa7lgE3iqL4y6grDwHPfHeEHw9V8Ns5A3nvtvGIwAML9rSZ9G485mz448kZpQxTkBGnoaSua3cdn1x6iG/2ljGudxzLD5zk2ne39Nhcz87wxpp8shIieO6qkTxz+QhmDUrmxR9zz1jhPBA2HKthU34Nj18ylIX3TGH+rydRVNPMP5Yf8fm8x785xJrcKh6bO5h3bx1HslbNbz/fx43vb2NHYV3Iy+ObzTZeXpHLvZ/u8quU3Wyz8/KKo4zoFcOf5w5h7og0bp/al8W7SgK+2HVErd7MfZ/uJjFKzZo/nMP6P53HgBQtjyzaG9R7rFxnQqtRunIL26P1Q0iuN1g8NlaRhNpAnTlSyWtsSyxFXIujN5CFYUcNiKC1Izl0e46l9UYy4yPcRIzEEC5sVxyqIClazeR+zl3xEb1iSI/VsLIbFy+eWHWkEptD5OIRaR6///Tlw+mdEMmjX+xzlVV3F6X1Bn46XMGNE3t7FTEvHpmOQ3QKaf6wr6SB1Bg16bHeF+ma8DDumZXNhrzqoMVJgGX7TmK02rl2fFaHj+0VF8F7t03gs7snMzwj1udjpw1IxGJ3sMeHO2flYefv+VIP7qcwhcANE7PYeKzG52fhKyuOUtts9mtM3vjrJU5n9d2f7OLPXx3g+wPl/O78Qa7jKcMUXDwijbVHqzrc3KrQOWNMbpyY1cZ9+LvzB9E3MZL/++ag367W1izYVkx+lZ6XrhlF/+ToNt8LtAQ5TCFw4fA07j2nP9eMz2TWoGSevXIkV4/txZtr8ymo1nd8kAD58WA5d32yE4vdwfQBiXy1p5Sr39kSsMMwEA6UNrDuaDUPzxlIn8QoNOFhvHPrODThYdz/2e42zsxPthShUiq4fkKmx2NNapkD7yryvXmlM1i58+OdmCx2LhiWxsdbinhwwV6Pc43dxXX8Z/UxrhyTwfUTnILEXy8ZQkR4GG+sye/EK/ePjh3J4dgcIiar73mSzmhFE67wKD5Fq4NzJHtq4BemEIhShXXakVzd8p5L8hDLlRCl6tJoi4SOHMlBOLgrdM7X01GzPWnTPxTNeyVHci8/oi3Av7lcg8FCXJT392NitIoGgzWgeXt+lZ7eCZGuOduoFkH5UDc0gzPb7Hx/oJyLhqcRqWobnTahTzy94iL4dl9o+h4Ew8LtTuPSLZN7d/BI3/RPjqJvYmRI4y3KGowhmevtOVHPgu0nmNQ3AZ3Byqur8oI6zvcHKhAEuGx0Rpv7J/SJp8ls41iAPRVkup7XVx/j4v9s5PxX17u0LX94dWUeUaowNv9lNn0SI3nmuyMBm9G2Ha8lMUrFoNRot+8lRatJilZxtAdGmgbjSEYUxUpgOk4x+QHgkCAIjYIgFAmCUNDBzXPHEj8RBKGfIAjPtr4BV7d6yOz23xcEYWyQp/sRGN/y9UmcuciXCoJwpY/bhZ14eV2CyWpn74l68qv0Ab2xtx6vZcH2E9w7K5tHLxjERcPTeOXaUeRX6ds4UlYeqSQpWu0qC2pPZlxkl0Zb7C6uZ/GuUu47pz8f3TmJL++bSoXOxLvrOufCCiWiKHKi1tAp1+ChMh27i+v59fR+qJQKFAqBZ68YgcXu4M21PaeEu7uYv6WIpGg1N0x0TnCmDUjinlnZLN5V6nVh99PhCr7ZW8boXAGkAAAgAElEQVTDswfywLkDmDsinaUPzuD5q0ZytLKJ69/byqinV3L9u1v5bv/JTruUHQ6RBxbs4Z31x9ld3MADC/bw5hrfv7uF209Q1mDksYuGuBx595/bH6VC4I0OnhsINruDBxfuobbZwnu3jSclRkNsRDjv3DIOi83BU8sOBXzMsgYjGT6ELleeoY/Jn9OR7L6wCtaR7Fp8tojTLkdvAAtDXx3o24/Pn472/lJSb/CYN5sQpaI2BM1/RFFkW0EtMwcmud5rgiBw3pAUtuTXYOtBmcMrDlXQKy6CUZmehcEotZLXbhxLZaOJ+z7d3WUOMn+Yv7UYQRC4fWofr48ZkqYlI1bDaj8XVvtKGtwacnjijml96Z0QyWNLDgR1/bE7RD7YWMDwjBjG+XA/B8PEvgmEKQSf0RvfHywnMz6Ckb08/56vn5CFQoDPd3p2JR8s1bFkTyl3Tu8XtIgMkBkfydu3jqO4tpnFu0q5dUpv7j+nf5vHXDwyHbPNwbqjvhcg3+wtw+YQXbmJEhGqMP5x5QiKaw088e2hgP7edAYrr60+xvQBicwekuL/CwuQ/7t0KKowRchFzJI6A3/4cj+js+JY9tB0/nPjWBbcPYXyBhO3fri9yzaDPt5ShFatbCOMpMdG8NqNY8iv1ruue4U1zXy+8wTXjOtFopeoprhIFQNTojvMV31n/XFq9Gbev30Cb9w0lmeuGM7POZX87vN9bX7nFToTjyzaR0achmeuHNHmPLdN7cMPB8tdufmeqNCZWLyzpFPu3MYOhGSpT0BHOckNBovX48QEkJHbfmzOMbg34u20I7nls9KTIzkxSkWTyRbyGDRRFP0SkoNpTljR0kAv3Y9oCyAkDfdK642Ehwk+q1Lg1O/Pn6zteoPVa6wF4Mq0DuR6f7xaT3arjbf4KBUZsRoOnzz9os3a3GoaTTauGJPh9j2FQuCy0RlsPFbTLVmpzWYbn207wQXDUsmMd5+HBoIgCMwZmsrW47Uhier496o8pr+4hnNfWdvpDYAPNxYQGxHOR3dO5JKRaSw/UB7U3/oPB8uZ0CfebfNGmsscLus5omCt3syeE/U9MtrxdHHkZKOr50V6nIanlh32K3qqusnMzzmV3DSpN73inNFpuRVNbM73P1JOFEVnPnL/RK+b/kPSYs6YaAsEQRgNHATGSXcB0UBvoK8ft87QB3i83e2yVt+f6eH7o4M819RWX2fgzEb+poPb+0Gey8XJBiN/XnKAv317qFOTZ1EUmb+1iMnPr+aqt7dw/qvrufKtzX69Ee0OkX8sP0KvuAgevWCQ6/5zB6dw7fhM3l1fwOGTOmr1ZtbkVHHBsFS33EeJrISILm2299bafBKjVDw825l7OCozjstHZ/D5zhMhaVzTWUrqDFz19hZmvbKWCc/9zJ++3B9U/tjSfWWEhwltSqN7J0Zy7fhMFu8sDWmn5V8aOqOV9XnVXDO+F6pW3cUfmT2Q9FgNf1t62G1R3mCw8Pg3hxiWHtMmMzNMIXDz5N5seOw83r5lHDdOyqLeYOHhRXt5e12n9sFYtv8k6/Oqeeby4Wz762yuHJPBP1fmseKQ5w7RerONN9fkMyU7oaWhk5PUGA03T+7N13vLfC4kA+HFH3PZVlDH81eNdJX4AfRNiuLRCwbx0+FKVhzyvxkYOD/LMuK8LyK0fpShNhisHhv0RAUZHeFJBA60C7srm9FHRnJ0FzqS25MYrQoo49kb+VV6avQWpmS3rS6Z1DeBZoud3B4yiWk0Wdl4rIaLhqf5dFqOyYrjpWtGsftEPfNe39ilzkZvNJqsLNp+grkj0sjwUeIrCALnD0tlfV51h9f9+mYLxbUGxmS5x0m1RxMexn9uHEON3swVb23mzTXHeHPNMZ5ceoh7P93Fgwv38OKPuaw7WuXRxbVwezGFNc08dN6AoBrr+EKrCWdEr1i2eGlQ1mCwsDm/hktHuceXSKTFapg9JJXFu0rdxi+KIs8sP0xCpIqHZgeWi+yJ8wansOuJ89n619k8e+VItznPxL4JJEWr+MHH56Qoinyzt5RxvePomxTl9v2ZA5N5ZM5Aluwu5bef7/N78/LNtcfQGa08fsmwkP+eWpMUrebGSVksP3AyZH9PoijyxLeHEIC3bh7ncuJN6pfA+7eP53i1nvs+3e0z/iEYjBY7Px2q4JKR6W5VMzMHJvPAuf1ZvKuUhxbu4c6PdqBRhrWZD3tifJ949hTXe12Amqx2Fm4v5pKR6a7r7O1T+/L4JUP5/mA5f1pygGazja/3lHLp6xvRGa28dfM4t2vNbVP6IAALvcS66AxW5r2xice+OsDj3wS+Cew6jtHaJjqiPafiqXx/ZvlyNkerlZhtjoBFDG+VQYE0b/OGr0bBUhVBqGNXjFY7ZpvDj4zkwF9fZaMJlVLhtUmdRKo2dEJyWYOR9NgIt0ii9vjTdFnCWaHmS0h2fs/fzyaHQ6Sotpnsdp/FwzJiOXzy9DuSl+4rIylaxYwBnnPsLxudjt0hdkuF2Bc7S9AZrdzbbgM1WOYMTcFid7DxWPDVUgA7Cp1VGzMGJKEQBJ793ncVqi+aTFZ+zqni6nG9iFIruXxMBjqjlc0BRhXkV+k5WtnEpSPdK6n6JUWhUirIKe9+IVkURT7eXMjUF9dw9dtbuPqdzZ3Ohf4lIooiL63IRatR8uZN4/jjhYMpqG72K9bxh5YGvNeOd1YqXTEmg9iI8IB6nhTWNFPRaPKYjywxOE3L0cqmHheJErCQLAhCb2ANkI1TQBYAK1ABFPtx8x1md5bTbLZxw/tb+WpPKZ9uK+auj3cG1Z1ZFEUe//YQTy49zKjMWN69dTz/uGI4ZQ0mrnt3S4c7dl/tKeVIeSN/uXiIWynaE5cOJT4ynIcX7eWPX+7HZLNz14y+Xo+VGR9JdZM5qFLNjiisaWZNbhW3TOnjEpYAbpvaB4PFzo8HPQt0p4vqJjPXvbuVwppm/jZvGL+e3o8le0q597PdAX0YiKLI8gPlnDMo2c2def85A7CLIu9v8O3AbjJZeWjhHgY98SM3vr/1jOrAvvFYNTaHyAVD22aKRamVPDlvGDnljXzaLkv6meVHaDBYeOW6UW3EZ4kYTTiXjEznqcuGs+J3s7hyTAav/HSUg6XBTS5FUeT1NccYmh7DLZP7oAxT8OI1oxiVGcsDC3Yzf2uR23M+2FBAbbOFv1w81E0cuHdWfxQCfLCx8877b/eW8eGmQn41tQ/XjHcv2717Rj+Gpcfw1LLDfk32Jcp1Jp/imd/RFh4WViqlApUy8O7lkkjXemEeaOah6xgR3hfYUWrn52aoGqM0mqzojNY2jfYkEqPUIXHc7ixyOumkWAuJ8X2cguWeEz2jQcianCosdgeXjvIca9Gaa8ZnsvjeqVTrzbz44+lpUNWahdtP0GS2cd+sjhdf143PwmxzsLSD0tV9Lc2B/HEkA4ztHc/Ce6YQFxnOP1fm8c+VeXyzt4zCmmZyTjby4cYC7vhoJ1NfWMPzP+RwrKUPwraCWp7/IZcZA5KY6yVCpLNM65/I/pIGj38nrlgLD4ux1tw8OYsavZnV7fIWl+47yc6iev5w4WCfmz6BEKlSeo0TkeIg1uRUeZ3vHClvJK9Sz1XjPMcjAPz+gkE8Nncw3x8sZ8H2jqfMJ2oNfLKlmGvHZTIsI8a/F9IJbp7UG6td9DsPuiO+P1jO+rxqfn/hYLfrxcyBybxy7Wi2FtTyu8/3hVRMXp9XRbPFzuUe3H8Af7hgMPfM7MfKw5UYrXY+/NWEDt2V4/vE02iyke8l+uPnnEoaTTZumti2NPyeWdn88cJBfLO3jOFP/cTvF+8nKyGSJfdPZZSHar+MuAjmDE1l8c4Sjz+Tt9blU9dsZkp2Asv2nwwqikQURb+a7QHojL6vczqj1dWXwNsxAt0UPrWh2/Y6HAohWRIiPbmDpfvqQyy4SFVFHWUkazXhAf+synUm0mI0HW4yxUQoUSsVVDWFItrC0GE+MgTWINFb1JmE5Eiu8dMYcFJnxGR1tHEkgzPSq6Cm+bQ2ttMZrKzOrWLeqAyUXjKgh6XH0Dshkh+9mE+8YbE5WLC9mC93lQRVWWaxOfjvpkIm9U1gnId+SMEwsW8CWo3S7bodKP9elUeyVs0Ht0/ggfMGsK2gLmhX8uqcKiw2h6uR4LT+SYSHCWwvCKzXxg8HyxEEZ5VSe5RhCoakacnp5piCJpOVRz7fx9PfHWHWwCSevmwYOeVN/HPl0W4dV3cwf2sx6/OqefT8QcRGhjN3RBrxkeF8u6/jxnnr86rpmxjJwFRnjrFaGcZFw1NZdaTSb91Lqsqbmu1dSB6UGo3J6uhx2k0wjuTHAelTZAUwDYgURTFDFMV+/tw6M2BRFNeJoigEePvYw3HuaPX9p72cK9DzCKIo9u3M63vlp6OU1htZeM8UXrl2FLuK61m6P/A8pDfW5LNw+wnuO6c/8389ibkj0rhtal++fXAaWk04t/53u9eJpd5s45WfjjK2d5zHrqxxkSreuGkcZfVG1h6t5r5z+jMgxb2DtURWgnMi0RWu5E+2FBEeJnDrlLaT8jFZcWQnRfHN3u7LkrLZHTy8aA8NRgsL75nMXTP68bd5w3juypFsyKvm3fX+u1sPluko15mYO8L999E7MZIrxmSwYHux1114h0PkoYV7WXGognkj0zlc1sidH+3sEnG/O1iTW0VcZLjHho9zR6RxzqBkXlqRy5GWUrUfDpbz9Z4yHji3v1/lzmEKgX9cOYL4yPCgL7L7S3UUVDdz57S+LiebJjyMRfdMYfaQVJ5cepjvWnV7rWoy8cHGAi4dme5RMEqL1XDlmF4s3lXSqTK3FYcq+OOX+5nUL4En5g3z+BhlmIIXrh5JdZOZ57/P8cslZ7TYqWu2+BSSVUoFmnDvYrDR4nToeHPRRKuVwUdbtFocJ0YF5uht9CBGexobhK7ZXmmd1AHdc7RFvcHa6eiJQyd1xGiU9Else47M+AhSY9Ts7iGdpn84WE5ajIaxfjhywXk9uGtGNkt2e4+56QpMVjv/21TI9AGJjPQSwdGakZmxjM6K4731BT4Fs30nGlAIeI318MT4PvEsf3gmh/5+EUefncvBpy9i5aPnsOaP53Lw6Yv44PYJjOsdx/82FXLBvzcw4dlV3Pj+NlJj1Pz7hjFd5nKdmp2IzSF6jAPoKNZC4pxBKaTHali0o8R1X1WjiaeWHWZMVpyrceTpYO7wNIxWu1eX1Td7nJVF8zoQx+8/pz8zBybx3Pc5FNY0+3zsCz/mEKYQ+GNL476uZmCqlgl94vliZ0mn454aTVb+/t0RRvSK4Vdeol+uHNuLJ+cN48dDFVz51hYW7TjBgu3FvPJTLn/8cj8fbiwIai6zOqeKGI3SY38PcJaSP37pMA7+/UK2/mUOk30s8iQm9JVykj1/Vi7ZXUp6rIapHpxHD80eyBe/mcIjcwbyzi3j+Pr+aa5u7Z64bUofapstbhVNRoudz3ec4JKR6bx8jbMgc32e/3mPEgaLHXsHTWX9jSXQGb037Yv209XcnkaTFYUAUar2QnJooi0SolQem7pJ85FQxyVJ4m1yjOfoFIlotTKgDX2AyhYhuSMEQSA1RhOSvitlDcYO85EhwIzkZs9RZxJS7Iy/c+KCaudna3ZyW0fy8IxYRJHT0tBS4rsDJ7HYHC5noycEQeDiEWlsya/xu2JZFEXu/2w3j39ziD8tOcBLKwLfUJ+/1dlo9oHzQuNGBggPU3Du4BTWHq0KyjAHTufv1oJa7prRjwhVGFeN7YVCgJWHgzORrcmtIila7ZpbasLDGJ4Ry+7iwIVkT7EWEkPTYsgt97/Cr1xn5Dfzd3HHRzs4UBp8E0idwcr2glr+t6mQS17fyA8Hy/nTRYN5/7YJ3DG9HzdP6s3CHSco13WfWGm1O3jlp1xu/98Odp6G+fqJWgPP/ZDDeYOTuXN6X8D53rxkZDqrjlRgsHj/XDJZ7Ww5XsM5g5Lb3D9vVAZ6s83v6+6W47WkxWjo56FKTULqe+Ftk7q7CEZIngOIwGZRFC8RRXGbKIpnhhrVzewqquOTrUXcPqUPk/olcM24TIakaXl/Q2FAk/W1uVW8uiqPa8Zl8ue5g9ssADPjI1l0zxQUgsA983d5nGy9uSaf6iYzT1023OvicWr/RDb9eTY//namq+u4NyQHXahzkhtNVr7cVdLSLb3th7UgCMwdkcaOorpua7T0z5V5bCuo47krR7YRK2+alMW8Uem8uirP7wvCysOVKASY4yX78MHzBmC2OfjAiyt50c4TrM+r5unLh/PqDWN4/eaxHK1s6tDF3FWIosja3CqeXX6ET7YU+fyg7giHQ2T90WrOGZTssYROEAReuW4UsRHh3PzhNn6/eB+/+3wf43rH8WAA5c5aTTh3Tu/H+rxqimt9L+w98e3eMlRKBXNHtnX2RamVvH3LOCb0iedPS/ZzoLQBs83OHxbvx+YQfYoD956Tjdnm4JMtRQGPB5wNyx5auIeRmbH891cTvHbCBhidFcc9M7P5fGcJDy/a2+HCXfp79xTF0BptS9d3TzQYnQs1b6WM0erAswK9RlsEsCisN/geF5zqHh8yIbnl5yltzLUmMTo0DqnDZTpG9Ip1+9wXBIHxfeK9iiOhYk1uJY8s2ssT3x702jxNb7axLq+auSPSvMYpeeKROQNIj9XwrJ8bIaHgv5sKqWoy8+C5/n/OPHr+QMoajPx02LtLZ29JA4NStW2qcPwlWq1ErWxbZRTR0iH+/dsnsO3/5vC3ecOYMySVP88dwncPz/BY3h0qJvSNJzxMcOtyXd1kZlMHsRYSUtO9DceqXQ1S/7jkACarnX9dP7rD0upQMiU7kRiNkp88LGStdgff7jvJeYNTOixfFwSBl68dhTpcwW+8zNXAKRD+eKiC+8/t32EjrVBy06TeFNQ0s72wcwu9V1YcpVZv5vmrRnp14QH8ekY/3r9tPE0mK3/9+iCPf3OId9cXsO5oNc9+n8MN720NSEx2OETWHq1m1qBkn+cFp8PI38+avomRJEap2OVBeKhqNLEhr5qrx/Xy+p6cnJ3I7y8YxMUj0zs854wBSfRJjOSzdtVW3x04SaPJxq1T+tA7MZLspCg2BCEk+9MLwF83qc5HRnKwjXN1RisxEeFuP6dQRVtIMQntSeiiaIvqlgbhKR183sa0NNsL5DpW0WhyNdLriNQYdaejLUxWO1VN5g7nf9C6Ms33/MVqd9BktoU02kIyVLkLyc4NnFDkJDscIh9sKOCm97fx71V5XiNcluwuZUia1nVub8wdkYbNIfrt5P1qTxmrc6t44tKh3DQpiw83FXI8ADGqrtnCf1YfY9agZDfBrLOcPzSFGr3FVWUVKF/tKSVMIXD1OGfkY0KUigl9ElgVRBM/h0NkU34NswYmtflMmdAnnv2lOr+rYY5X68mt8BxrITEwNZraZovfGx5PLT3MyiOVHCjVceuH2wNutH60ookr39rM6GdWcsP723hm+RGiVEo+/80UHjxvgOv13jMzG7sjdNVGwfD22uO8tfY4G/KquffT3V0eSff5zhPY7A6ev3pkm7nmxSPSMVkdPrOOdxbVYbI6OHdwW21mWv9E4iPDWX6g4zhIq93BpmM1TBvgPR8ZcFVNHK/65QvJUkDrp6EcyNmOyWrnsa8OkBEbwWNznd3BFQqB26f2Jae8kT0n/PuQ1ZttPP7NQQalRvP81SM8vil7J0by1s3jKKo18LvP97XZCcytaOR/mwq5dnxmh2WzyVo1Q9NjOlzkSQ660hBluUos3llCs8XOndM9m9znDE3B7hCDmkB3xNGKJp5edpg/LN7P0n1lbk7Anw5X8O7649wyubdbVIAgCDx31UiSo9U8tuSAX86JVUcqmdQvwevis39yNFeN6cXHW4rcnARVjSZe/DGXaf0TXQ1lzhucwiUj03hrbX7IMnb9xe4QeWzJAe78eCfztxbz1LLDXP32FlcmXaDsL22gttnis8FQilbD4nunMiRNy4pDFVwwPJX/3THRTVDpCKmxU6AXWavdwXf7T3LB0FSPLlaVUsE7t44nIVLFte9u5ZyX17HxWA3/uGK4zx3KASlaLhiayidbiwN25q7OqeSBBbsZ3iuWT349yS0j0hN/uXgIf547hOUHynnhhxyfj5Um6P2T3TvQtsbXoq++2fm34SkjGZwivD7ADGJPDXoSo1Q0GK1+x83ojE4nlNZHdmREeBhhCiFgodsbJfXeHcmJUS0unE7kJFvtDnIqmtrkY7dmfJ8EyhqMIXEqeeLfq/L49ce72HK8hiW7nfmgnmJkfjpUgcXm4JIOHJ3tiVQp+d35A9lX0sCq05AvWK4z8uaafC4clso0L3mHnpg5MJm4yHCv1y2HQ2R/SYPH6otQkBSt5q4Z/Xjp2lHcf25/vz4XOkOkSsmYrDg2tXPwfrO3FLtD5Dof7qzW3DWjH30To7jjox1c9O8NbMir5u+XD+/w8yfUqJQK5gxN5eecSrd5wYa8amr0Zq6b4J9DOj02grdvHkdBTTMPLnTfvDNa7Dy59BDZSVHce052yF6DP1wyMh2tWsninSUdP9gLa3Or+HRbMbdP7esxvqE9Fw5PY8OfzmPdH89l21/ncPQfc9n1xPm8fcs4DpTpeHmF/9VCx6r01OjNzAqxMCJtum0vqHMT+pbtP4lDhKt9xJoEgkIhcOvkPuwsqnflbYqiyIJtxQxMiXY5rSf2TWB/qS7gDTT/hOSOG+ZKx/LVbA+CibawepxPaTXhNHY62sLiiklojyRk1oVYSJYcyR3Fp0RrlIgiNPvZa0UUxYCE5JQYTaejLYprDYgiPuevEv46kqUN/IQo35VgKqXC7+bDBTXNRKuVbk0V02M1xEeGh6Qh2jPLj/DcDzlUNJr4z+pj3Och2jC/qol9JQ1cOz6zwzX16Mw40mM1fsVbWO0OXvs5j1GZsdw1ox9/uHAwqjAFH24s9Hv8r646isFi52+XukfsdZZzB6UQphCCirewO0S+3lPKOYOS2/zNzBiYRE55Y8AmsiPljdQ1W5g5qO18bULfeCw2B4f8fC+sbDEBXOQjDkyKQcj3QxQsqNaz8kglv79gEEsfnI7RaufjAMxD5TojN32wjbIGI3+6aDAf3TGRLX9xGgEn9m1bjdM7MZLJ/RK6rZq7Vm/mrXX5zBuVzspHZ9FgsARtlPIHm93BV3tKOXdwiltk2aR+CUSrfUevrD9ajUqpYHK7vjLKMAVzR6SzOqfjeIudLYbHC4el+nxcQpSK+MhwCjqoUDvdBCMkS6ub4L31Mm78a+VRCqqbefGakW1cRpePyUATruCbvf4JV6+uzKO80cQLV4/yKZJN7Z/Ik/OGsTq3ij9/dQCzzU6FzsT9n+0hJiKcv1w8pNOvSSJFq0alVIQ02sJic/C/TYVM7BvvtWR4TFY88ZHhrMkNfGfSFysOlTPvjY18vvME6/Oq+O3n+7jotQ2sOFSOKIqsO1rFbz/fy+jMWJ68zHNUQGxEOC9cPZJjVXpu++8Onx80xbXNHK1s4oJhvjMqH71gEI6WHN7W/H35Ecw2B89d1Xa37YlLh6EQBJ5ZHnxjgmB44YccvtxdysOzB3D4mYv46M6JFNU288iivUGVN0mNmmYO9L0g7JMYxee/mcqRZ+by1s3jfJbHeSMtVsOEPgn8HOBu9+b8GmqbLR47MUska9V8+9B0rhufydB0Le/fNp4b2uUoeuKB8wagM1p5LwB3+drcKu7/bA9D02OY/+tJfueHCoLA/ef259fT+/HJ1mKfmzT/z95Zh7d13l/8XDHLAjPGMSZ2yOE0SUMLFFJauSlzt67r2m2FrbAO2lG3tut+3VbGlDkNNGmYyZA4dswo25IlWyzd3x/SlUG6uvfKchy4n+fx080k2ZHvfd/znu851M0uUqHUYDQyMe2YJuX4ofu3UktF6HNxWyz2OjyQigRDst/1SglIcmCjwoQ56K6K5hgjCAJqGfcRVDqazXYoJMKI+YCUQ4pLYeBw6rv64fb6UZwaOaZo+ijmJH92qAXPbzyBK8oysONXS7Dh5wuhkYux5n+7UdM5dPzvzV0NyDUqQ8+HC5dPy0BuohLPrTvO+tCgq8+F5zecwOK/bEb+o19jyV82Y+2+6CP9JEniN59VwEeSeOyCyPcAOoQCAvPGG7HtRFfEx6jr7kevw4OpLPORzwSWFiejotUamvQgSRJr9zVjalZC1NiswahlYrx12ywsKkyCXinBC9dOxdUzma+fo8Hyicmw2D1hbt21+5phVElwfiF78XJunhG/v7QEW0+YcPOre0PXRLfXj59/cAiNPXb87pISzoeiI0UuEeKiKWn4urwtpmtcs9mOBz44hOJUDaf1pkBAIMeoRIpWFnISrypNxVXTM/HmrvrQ5AYTu+sC64bZ45jjKrgyP9+IFosjLJLk88OtKE3XxvVw44qyDEhFgpAreWdtNw4392LNnOzQeq84VY2efjdncbA3wqHrcKiPRRMBPT4/+t0++ogqDtEGg7E6vRF7CjQy0YijLUw2F+0kBvVzWOKckdxpdUEoIGBgLNsLPD7bQ2qz3QO31896YiFFI0OH1TmiyZ26rqDT18j8WhcLgxFnDP9m1O872tqdIAgkqqQwcYi2yE1URpzCmpimRUXbyAr3tp3owms76nHT3BxsenAhnlo9EZuOdeLZYfESr24PxDTS5bUPRiAgsHxiCn6oNjEaSL6r6ECz2YGfLM4HQRAwqqS4cFIavjzSysphe7zdhnd2N+L6WVkh8TOeaBVizMk14OMDLZzz77fXdKHD6gqLAqE6PQ41cZOpqOi2mWEdIfrgx9lN36yvbEdpupa2SwEA8pMCfxcnWAjJXx8NuFp/PD0DmXoFfjQhBZ8cDC8XpuO5dcfR5/Li3dsD7uNFRUlIS5DTHgr8aGIKak39p9xkBgDv7W2C2+vHz5bmo4I2My4AACAASURBVCBZjYUFiXh/b2y53mzYeiLwGroywuG+RCTAggIjNh6jj17ZUm3CzBx9qCB4MBeUpsLu9mHz8ehmxvWVHZCIBIwaBhBwJZ8NjuS9wf9Gry7mYeRERx+e33ACT35RgVe21uGG2dlhLySVVISlxcn46kgbY6Nxi8WBt3Y14KrpmaELaTTWzMnGT5fkY+3+Zsz9wyYs/stmdFidePn6abQn8bEgEBDISJDHNdris0MtaO114p4oI8NCAYFFhUnYfLwzbi2XJ019+MXaI5iQpsWOXy3B3keX4uXry0AQBO566wAmP/kdbnp1L7L1SvyXwfG6qCgJL147FYeaLPjr+mraz6NOnZlOqzL1Clw7Mwvv7WkM3fC+ONyKr4604SeL8sKcAWkJcvx0ST7WV3ZgwylqAN5R0xUqdXvwR4UQCwVYVJiEJy6aiJ0nu/FhDOM0u052ozBZHbEUZTRYVJSEyjYrJ2fmpmOdkIuFjO6nJLUMz1xaildvnokfTWRXbjUlM5Bl/u8ttWhhEcK/pdqEO9/aj4IUFd68ZVZUtxEdD68oRF6SCg99eJh2vLPO1I8ktTQ0tkpHNEeyJbiR1dE4UFQyEfo5OpJ77eHOKH3wesc23sJs90Qdr6TQyMQjHrGlaOy2I0uviLj4o8Y5u0eQ2UiNOuYlRt4sFKWqIRYSOBpjiQkdnTYnHvu0HGXZOvzxslJIRAJk6BR45/ZZEAoEuPF/e9EZHPn9odqEQ00WrJmTzSnWgkIkFODBZYU40dmHT6M4LkiSxP6GHjzw/iHM/cMm/G1DNVK1MtwybxxUMjEe+vAIHv+snHaj/dbuRqyv7MDDywuRZQh3kDNxXr4R7VZnxPHTg8HppKlZZ4+QfEGwi4FywRxssuBEZ1/ExX000hPkePG6afjw7rm4cBLzhny0WFiQBLVUNOR+ZrK5sPFYBy6Zkh41QigSV83Iwl+vnIy99T1Y9OfNeOD9Q7jgH1vxTXk7Hl1VzMnxHk+ump4Jp8c/JNufDeUtvbj6/3bB5yfx0nXTwgqdY+EnS/Lh85N4h0U5IQDsPtmDNK0sYlTQSKHu84MPWk+a+nCkuTfqYXIs6JQSrJ6ShrX7mrG9pgtPfVmJFI1siOu9ODUwKk+5ltnCxpEsFQkgFhJRDxOsDN+HmnrgeihM70gWweX1M+6ZotHV56LdB0lFQiglwrhnJHdYnUhUSRnvbQMOXna/L2qtyiYjGQhEW9jdvhHFctUGs4fHJTI7kgEq15rBkdzPHCkGBKK+WDuSTX3IpTE7TEzT4Hi7LebXkd9P4ndfVSLboMCvVhaBIAJTxtfPzsK/fzgZMojVdNrwwb4mXDk9k9GNTrGiJAUurx/fH49uanl9Zz0y9fIhE5sXT0mDzellFLhIMvD8VVIRfrZ09CSfOxbkoq3XiTd3NjB/8iA+3N8MrVyMJcVDp1EnZyZAQIBzp8f+BjOSNVKkDXPuJ6qlyDYoWEW7mWwuHGyyYGlx9P16qlYGpUTIypG8vrIDUzITQsL0hZNSYbZ7cJiFUN7W68CnB1tw45xs5CWxO8CkDro3j8I0NxOfHGzBzHH6kIHg8rIMdAZ/p6PBu3saoVdKaCealxQlw2RzRdz3tFocONHZR2sMmJ2rh04hxjfl9PEWJElifWUHzsszsoqqG5+oPCscyS8BIADcRBDEqVFuzlIEAuBvG6rx6vZ6XD0jk9a9eunUdJjtHsaIhhc21QAILKjZQBAEfr6sAG/eOhPn5Rtx8eQ0fPGT80JlIfEkXSdHU098HMk+P4mXt9SiOFXD6OxZXJwEs92Dg3Fw0Tk9Ptzz9gGIhAReum4a9EpJKIv52/vn488/noyVJal4/MIJ+Oy+eazE+BUlqbiiLAOvbad30nxxuBWTMxOQqWcWJH6xvBDpOjlueW0ffv3xETz4wWFMz9bhzoWRCxJumz8OBckqPP5ZeUissbu9eGNnPW59bS9+81n5iLPSKDw+P574ogKZejl+vap4yMeunJ6JqVkJ+NsG+vwwuu+5v8EcNlYymlA3HKYFHAVJkth0rBPz8gxx2TBHgvp9/jaKuAUAW0+YcPsb+5CXqMJbt86CNkr7dTRkYiH+ftUUdPe58din5RE/52RXP6uxxmiOZMohTNf2Hoi24LbZsbk8YQ4rygHEdvNhsbtp3VWD0chFjCO/bGnosYeV4FHoQ88/9nFUakE7PCuQQioSoiBZHTFuYiT8/qsquDx+PHvFpCFZpdkGJf5303T09Lux5r978G15Gx755Cgy9XJcMyt2p+nKkhSUpGsiXmusTg9e2lyDJX/dgsv/tRPrKztwzcxMbPj5Qrx922z8elUxPrl7Lu5ckIu3djXiN59VhDkV9tT14OkvK7GgIBG30MQuMXFeUBj8oTq8sO1goxlqqeiURzaMJhk6BRYXJeG1HfWw2N3487rjSFCII5b9ngnIJUKsnpqGr4+2hfL9XttRB6+fxLUxvnYvnZqBz+6bh1njDNhZ2w2lVISXry/DbfNPbaTFYCZlaFGcqsFL39fSilo2pwefHmzBH76pwk/ePYhLXtyOC/+5DR6fH2/fNovVPYIN6QkBseSDfc2MxgGSJLG7rhuzcqNnEsZKtkGJ/CQVvj46MHr+2aFWEARG5YDjlyuKoFOKcd1/duN4hw1/vLx0yFqDKuyr4lDuBLATkgmCCNzDo9znLAzfJ1RMG0NGcqTvyTZzl45+lxd2ty/qGj5BIWE9wcSWTpsLSQxFe8AgBzfLtQ+1hmefkSwLfl3s64mTpn4ka5iNBBRscq3NIUdy9LUX2/Lkrj4XWnudKKQptJyQpoHHR+JEJ7e/G4rPD7fiWLsNP19WMOTv8bcXTcTsXD1+sfYIfvtZOW55bR80MjHuZ7l3BwJxNUaVJGq8xbF2K/bU9eD6WdlDMtnnjTfAoJTgc4YDwM3HTdh6ogv3Ly1gzPQfCfPzjVhSlIRn1x3HV0faWDnhex0erKtox8WT08IMWyqpCAXJas77/gONZpRl6yLeE6ZmJuAwixznTcc6QJLAMgbjF0EQyEtWM762rE4Pjrb0YkH+wGHxnPEGEASwrSZyoe9gPtjbDD8J3DA7h/FzKXKNSmTq5djCco8bL2pNfajp7MOqQZEg8/MD3Uffs5gsJ0kSr26vw51v7sMHDFODANDUY8f6qg5cPSMTElFkOXRRURIEBCLGW1CaHJ1BTCQUYPnEFGys6qSdOq9qs6HZ7GB8vVDkJqpijgEdLTgLySRJbgTwLIDxAD4gCCL+sw7nCOMTVdjzaMDV+sfLJ9G6VBYUJEKnEOPTQ/QOqqYeO9bua8LVMzORnsDNYTE/PxHPXz0Vf7x80qhtTjP1irg5kl/bUY9aUz9+sjiPcRNAXYSYTl7Z8JvPynGs3Ya/XTUl7HcsEgpwRVkG/nTFJNx63jhOguHPlxWAIAKxJMOp6+pHRasVF7HcUKtlYrx962zkJirxwb5mLCxMxH9unE57kRQLBfjrlVNgsXtw6Ys78Iu1hzH3j5vwm88qUGvqw3t7m3DJi9vjIia/tasB1R19ePyCCWG/H4GAwP1L8tHW6+Tkbipv6YXd7cOsURhPpaMgWYX0BDnryJSazj40mx1YFCXDeaSkJ8jxyxVF2FDViX9tqY34OdtrunDb6/uQa1Ti7dtmxRTtMZiSdC1+tjQfXx5pC2tI9vr8qGy1hpxQ0YjqSGbYOKik3Et1bE5vWLZxKBqCpcPIYo/eHE6hltKL5Fzw+0k09tiRbYgsuiQoJCCIkbXI15r6kaaVRT0VL03X4mgL96xNOrbXdOHTQ624a2FuxHvPpIwE/PuGMjSbHbjrrQPodXjwwjXTRjTGLxAQeGh5EZrNDrwQjAHy+vx4e3cDFj23Gc9+exwGpQR/vKwUux9ZgidXlwxxcggEBH61sgh3LsjFm7sa8MgnR0PC1ZFmC259fS8ydHL8/aopMbmmgcD9MsegiLhRONhowZSshJi/9+nKA0sL0Of0YtrT67GjthsPLisY9Xzm0eTmeePg9ZP46/pqNHbb8b9t9VhVkhoqTImFiWlavHxDGXY9sgSf3jsPK6JkMJ4KCILA7y6ZiLZeB+58c3/YwcymYx04/7nN+Nn7h/C/bXU42myBRCTAg8sKsO5nC1jlInNh9ZR0dPW5GAWEWlMfuvrcoQzh0WD1lDTsqe9BU48dTo8P7+xpxHl5RtZiHhcMKim++Ml5eHRVMT6+e25Y8Y9WIUaiWhqKG2BLpD6BSGjk0d2kTII0dT/mmmtsddI7kgHuURkU1OFPtJJRvVIScsjGi06bi7FoDxjIlGb787VzFJIpV2znCNb9NaY+VrEWFOoohgIKavqNSdQ0qqTosjH/2+w+GZjcnE1jRKFK0mMp3HN7/fjr+moUp2pw0bDDI7FQgP/cOAMrJqbg9Z0N8PlJ/N+a6UjiUJYqFBBYNiEF3x/rpC0rf31HA6QiQdhkj0gowKrSQH4rXTQGSZJ4dt1x5BgUuGF2NuvnFQuBQvTJKEpR4953DuDCf27DN0ejC8qfHWqBy+unnVoqy9bhUKOFdVxip9WJZrMD02i6JyZnJqDD6mLcC6+v7EB6gpw2Im4w+UkqnOiIfk3eV98DPxko8aVIUEhQmq7FdhZC8jflbZg5Ts9pMo4gCJxfkIQdtd2c40ZGAtVdsmzQNK5WLkZZto6VhvPX9dV48otK7KnrwcMfHsHTX0bv8Xl9Rz2EBIEb5tC/vvVKCaZl6bAxwn5/S7UJqVpZKKYkEqtKUwMF4TTP/6MDzRALCcaJc4rT0UDCWUgmCGIBgK8BfAjgYgDVBEE8SxDE5QRBnE8QxAKmt3j/EGcySWoZYyO6WCjABZNSsaGqg9Z9989NJyAQEFGjHsaSbL0CFruHc/g9gCE3k+8q2vHHb6qwuCgJK1lsorRyMcqydNhcPbKTtbX7mvDBvmbctygPiwrjKwimJchx07wcfHKoBZXDFixfBkXVCzg4s7IMCnxyzzyc+N1KvLJmOqPgVZKuxTu3z4JRLcWmY52YPc6AD++ag80PLcLHd89Fr8ODB94/NCLxqLvPhb+ur8b8fCPtydvCgkTkGpVYu599eQ+VQTlj3OgUT0WCIAgsKkrE9pouVjdZSnCO9+tmODfPy8FFk9Pw53XHwwqQPjnYjJtf3YtxRiXeuX123NwFdy4cj4JkFZ7+qnLIiWt1Rx8cHh9jYSdAbUJpHMn9bsjEAtqDGZVUyLlk0Ob0hrlkDCEhmd1Jb0BIZutIHnm0RYfNCbfXjyyaqQShgIBeIUHXCKMtxjOMvpWka9Hr8MQl797p8eGRT44ix6DAPYvo71sLChLxw8OL8OrNM/DDQ4swOQ7ZwAvyjbhsWjr+sakGN/x3N5b//Qc8+kk5xieq8MV952HtXXNx9cwsWlGdIAJi8k8W5+G9vU249KXt+Nl7B3HFyzuhkYnxxi0zRxy1c16+EbtOdg8R53odHhxrt45a0d5YUpqhxStrpmN+fiIeu6AY14/y5nW0GZ+owk1zc/DO7kYseO57CAUEHr2gmPkLzzDKsvV49orJ2FHbjb9vCByGOz0+PPF5BW55bR+SNDJ8dPccVD21ApsfWoQP7pyDnyzJH/FBZiQWFiZCLCQYyzR3BQWkWbmjdwB9eVkGJEIB/r7hBP67rQ4mmwt300yGxYMktQy3L8ilvTZk6xVo6OZm5rA6PCCIQBdBNJi6AEJCMs09k4rH4F62FzkjecCRPDIhmYqMikSCQhxyyMaLtl4HK7GXa0ZyW68TBAFWIjUQiLYABgRorvj8JKrbbShiIaZRaFg4kqlyQz1jtIUU3f0uxj3LrpPdUEqEKKUpGB5nVEIhEYbty9jw/t5GNPbY8fCKwoiHviqpCC9eNw1VT63A1ocXsYqjHM7l09Jhd/vw6cFw801PvxsfH2jGZdPSI673L5qcBqfHjw00RWLfH+9EVZsV9y3OpzUixRO9UoIP75qLZy+fBIfbh7vfPoCfvnco4oQqSQYijErTtbQdSdOydLC5vKwyiIGB7g+66yd16BktTsLu9mLriS4sm5DMatIlP0mFTpsLvVGuI3vqzBALibDnNS/PiIONlqj7n1aLA8fabVgSg4np/MJE2N0+VnEe8WJ9ZQdK0jVhRr3zCxNR2WaNKuLXdfXjX5trcdnUdOx/bBlumpuD/22vC3UHDMfq9OD9fU1YWZoaNcsaAJYEOzzaegf2PV6fH9tqurAgPzHqv/Xc8QYkqaVYuy9c13B6fPj4QDOWFifDwDJOlm5idCyJ5eqwGcD3AC4HQAJIBvAggA8AbAx+LNrbppE+6XORS6emw+nxY12EMZb6rn58dKAF18/KHhW3QzygnHRUmQ4bPj/cimV/3YLxj3yNose/weQnv8Mdb+5HYYoaf7tqCuuRxIWFiShvscZ8un6s3YrHPyvHnFwDHlg2OjlR9yzMg0YmxtNfVoYWP16fH2v3N2Nmjp7xQhcJLo61qVk6fHbvPBx4fBlevqEsFG9Skq7FI6uKsaO2G18eoc/5YeIP3xwLNMxfOIH2340gCFwyNR27TvawyvoFAmPkuYlK1rli8WJhQRLsbh+rDK5NxzpRlKJGGsdJAa4QBIFnL5+EeXlGPPzREdz15n68vqMe97y9Hw+8fxjTshPw7u2z45olLRYK8MRFE9HU48Arg8r+qJILNkKyWiqC0xM5z7DH7oZBSX+DVUnFcHh8nIoY+lzeMBcTtdBmmzFstrtZZyTHw5FMCQB00RZAYCE+krK9ph47rVBNQW244pGT/PzGE2jotuOZS0sZJzj0SgkWFSbF7QCEIAj86fJJ+OmSfLSYHdDKxfjXddPw/p2zaTcmkb7Hgz8qxF9+PBl2tw/barpwyZQ0fH7fPGTouOciD+e8vMBCfrC7cmdtN/xkYDT1bGRRURJev2UmbpufOyqRA6eaR1YV46Hlhbh0ajrW3jVn1O8BY8UVZRm4cnoGXtpcizve2IeVz28NFUx9cs9clGXrh8TWjBYamRizcw1YH6VlHQgcQCeppciJIb+cLalaOW6el4OPDjTjuXXHccGkVMwZw7/bLIMCjRzLk3odHqilIsa1JFMXAFNGMkEQweki9vdKt9cPh8fH4EiO7d5rCrpZo0Vb6JXxjbawOT2w2D2s7h1cf76OXicMSinrbPakEUZbNHT3w+HxsZpIo2BTTGyxB4qS5ZLo6wWjSgKPj2Q8xD/SbMHkzATaa5NQQKA4VYOKVm7rna4+F/78XTVm5+pxPkMvilwijHm6qCxbhwmpGry+oz5MNH93TyNcXj9uponXmp6tQ6pWFnEClCRJvLCpBukJ8rhnukdDIhLgyhmZWP/zhXhoeSG+ONyKB9ceDnMVH2qy4Fi7DddEKdOlOiQONbETQg80WiARClCSHvk1OzFNA5GAiBpvsfVEF1xeP2t3aX5ywLhRY6KPtzjSbEFRiibsNX9enhFeP4k9dfQFgFT8Il3+bzRm5RogEhDYUcvseo4HJpsLBxrNWFYcbhCkTFhboriS397VAIIAfrWqCAIBgccvnIBFhYl44vMK7DrZHfb5L35fgz6XF3cuYI4GWxrM4N5YNWBI3N9ghs3pZew9oqbVvz/eGVZeuHZfE8x2D26cm8P4HCiy9ArIxKO/luJCrM+GGPQ2/P+zeePhyLQsHTL18ojxFn9ZXw2xkMBd549dVh4TOcbA4qiepSPind2N+Om7ByEVC3DXwvFYMycHF0xKxdOrJ+LDu+ZyKgijLkKxBMebbC7c8cZ+qGViPH/NlCE5U/FEqxDjF8sLsfNkN94OlsV8uL8ZjT123DY/tpzNeHHNzCxMTNPg919X0Z5+fnO0DTf8dzduf2Nf2LjNjtoufLi/GXcsyGVs/b1kSjqAwNgSEz4/ib11Pac01oJizvjATTZShulgeh0e7Gswx3QjjwW5RIj/3TQDDywtwPbaLvz28wpsO9GFny7Owxu3zBqVnLO5eUasKk3Bi5trQgcAW0+YYFRJowqfFNE2ReZ+N23RHgAopYHFVb+b/fhVXwRHslgogEYmYhUN4fL6YHf7oGPlSI5P2V4jJSTr6U+j9UpJzNEWfS4vzCw2sYUpaogE7Av3PjvUghV//wGrX9iG9/Y0hlzrXx5pxb821+LK6RmYN0ZFYWKhAD9fVoBNvzgfH98zDytLU2MSLy8vy8CGny/EvseW4dkrJrN2FjAxZ7wBQgExJEJn6wkTFBLhWelIPhsRCgjcuygPf7tqCidR5UzkmUtLcfv8cTjcbEGCQozXbp6BJy6eOGq9AHQsLU7GSVN/xKJKIJiPfLIbs0cpH3kwD68owuMXTsBDywvx3BWTxvRwJFuvRLvVSZvVGIleh4dVj4JaFr0LgIqoirZuV8vEnDKSKdEx0vOLNSqDwhR0JEdz8OoU8Y22oNZOGTrmwyZVDNEWqRxMRiqpCCqpKOZIu2PtAWGsmCZ7OBJqKbuyPTYH+NQBQFeUCTO/n0R1R18oP5yOiWkaVLZaWUckAIHeB7vbi99dUjKqf/MEQeCmuTk43mELTVkAgMPtw+s76jE/34gCmj2XQEDgwkmp2FJtCivM3nmyGwcaLbhjQS7nYth4QN03f7miCF8cbsWfvzs+5OOvbD0JpUSIi6OI3DkGJVRSEetYkgMNZpSka2hj02TiQEfIkSgdIesrO6CRiTCDZWQSVWxNV7jn95M42tyLSRHMDWXZOkhEgqjxFt8fMyE9Qc66ZG8wKqkIkzMTsL0mXIQdDTZWBbKlfzQxXIQvSlEjWSPFFhoNx+vz49NDrVhclBQylQkFBJ6/ZiqyDArc8/aBISLugUYz/rO1DldMy0AJzTTCYPKSVMjSK4bkJH9+uBVysZCxpwsA1szJgVBA4OVBsZM2pwfPb6zB9Gwdp4gtsVCA+fnMj3kqYZeCP5Qn4/4seBghCAKrJ6fjpc01aOt1hByq+xvM+OJwK366OO+UuzK5QAkgDSzaJhu6+/HE5xVYWBDI9x3pjaw4NXgROm7i1ALfa/fgltf2wmRz4d07Zo/67/e6mVnYUNmBJz6vwKEmC746Esg2YhvCPloIBQSevHgirvz3Ttz55n786/ppQ7Ir/7P1JH73VRWyDQo4PT5c95/duGp6Jh69sBi9dg8eWnsE2QYFfsqiSCLLoEBZtg6fHmxhjGmparPC5vLS5puNJiqpCNOyddh6woRfrSyi/bytJ0zw+clTJiQDgRvN/Uvzcd/iPHT3uaBTSkZ9MfjIqmJsOtaJ339Vhd9fVoqNxzpx7cwsVovowWOow0W4Hrsn6saB2jD2ubysD5dsTk9oIzYYg0rKSoilxtC0LB3JfS4vvD7/iBx5DT39EAkIpCXQX4OMKimq2rmPYAJASzCqIlMffRM7sJhmLh1ZV9GO+987hOJUDVxeP3718VH8+btq5BqV2FPfg+nZOjy1uiSm53suoJWLsbAgEZ8fbsUvVxTBR5JYV9GOhQWJp2TUlIeHC2KhAI9eMAGPXhC5NPpUsXRCMn77eQU2VHZg/MLwDfTxDhs6ba5TUtArFBC49byxNQJQZBsUIEmg2WxHXhK7yAG6MrvhMDmS2ZT2qTgW54bymyM4kjUjLNvrsrlAEIg6vaVTSGB1jvzeTtHcQwnJLA7fpSIIBQTrqMAOq5PzlEySRhoq4OZKVZsVAmLAccmGQFdG9J/HzDJSLCQk21y0maJNZjscHh8KU6I/x4lpGryx04f67n5W+fYf7GvCxwdb8JPFeaz/zkbCxVPS8Oy6Y/jLd8ex9q45IAgCr2w9iU6bC/+8ZmrUr71ochpe2VqHb8vbcfUgd+/zG04gSS3FVTPY75dHg7sW5qKxx46XNtciQ6fAtbOysLO2G18fbcf9S/KjFjkKBAQmpGpQzsL04Pb6caSlF2sY4rQmZ2rx9dF2kCQZtrfx+QOl6ouKkljvt9J1csjEAtqc5JNd/bC5vBHj3GRiIaZkJoTiHYfj9PiwvaYLV5RlxHyYMW+8AS98X0ObRR9PvqvsQIZOjqKU8L8ZgiCwID8R6yraI15vfzhhQlefC5dPyxjyfo1MjP+smY7VL27H1f+3C49fWAyX148nPq9AqlaGxy5kt1YhiECG8es769HW64BaJsaXR9qwbEJy1E4ZihStDNfMzMJbuxpwydR0lGXp8Pin5ejud+G/N07n/O+zbEIy/sPpK0YXzkIySZK8kDxGXDUjEy9vqcULm2rwzKWl8Pr8ePrLSiSppbhzFLPX4oFcIkSKRoY6FtEWf/muGiIhgWevoC8g5AIVHP91eRvrRV99Vz9ueW0vms0OvHzDNFYj+iNFICDwz2un4uG1R/DRgWZMz9bhhWumnhYjvtNzAjmIv/zoCNb8bw/ev2MOJCIBXtteh999VYVVpSn4x9VT4fWT+PuGE/i/H2rx6aEW+EkSMpEQ794xm7Uz6aJJqXjii0rUdNqiLsSocZWZo1iYE42FBYl4bt1xmGwu2pzz7yo6oFdKTsnrZzhCAcGpvGMkZOgUuOf8PPx1fTW21XTB4/PjirIM5i/EQJFPpI2oud+NcVFczVyzAn1+Ev1uX8QFKFtHL5WLyMaRPFjoHkkmaEO3Hek6edRrl04pjtkh1RwsQmWz2ZyRo8MH+5rh9vppBU2nx4ffflaBiWkafHT3XEhFAuyo7cZbuxrQanHgvkV5uHdR3il3K55pXDI1HZuOdYZyDLv63LhsGru/Kx6ec5FA0ZEGG491RlwXv7a9HlKRACsmjm1R4amGKltq6GYvJFud7A5oNXLmjGSFRBh1PR+INuDiSPaGHjvS9wJGlpGsU0gY77cAYHF4okZgsGXgHszsSCYIAlq5GBYHu/t9W68T03O4TbGkaGQxR1tUtdmQm6jidH/XyMVwevzw+Py0rxOz3c0qms2gYo4qo1zThYyO5IHCvWhCstPjw4vf1+CF72swL8/AyjgTD2RiIR5aXohffnQUf/zmGIpTvfUVPQAAIABJREFUNfjHxhO4YFIqYwZ8aboWuYlKvLunEVfNyARBENh1shu763rwmwvDS9FPNQRB4OnVgTLXxz8rx9GWXnxb3oZcoxJ3sIgkmJiuwXt7muDzk1GniStae+H2+jGNIad6ckYC3t3ThPpuO8YZh04H7qvvQU+/m5PxSyggMD5RRZvjTBk2JtOU0s4ep8cL39fA5vSEFRPvqeuBw+MbkYlpbp4R/9hUg90ne0bV0Nbv8mJbTReun5VNq3csKEjE2v3NONzcG5Yn/uH+ZhiUkoiF9rmJKrxz22zc/fZ+3PXWAQCBbOpX1kznNNl+49wcvLqjHn9eV420BBl6HR7cPC+H9df/YnkhNh834cb/7UGWXoFj7Tb84kcFMXW+LC0eW3PhcGJxJPOMEZn6wIncm7saMClDi0NNFhxqsuD5q6ewOhUZa3KMzGUfHVYnvj7ahpvn5SA5jiLY+YWJeH9fE/Y3mBlvrgcbzbjltb0AgLdum3VKhUqNTIyXbyhjvPGNBVeUZUAmFuC+dw7iplf3IFUrx0cHmrFsQjKev3oqREIBRELgVyuLcOGkVHy4vxkSkQA3zM5GJkP26mBWlASE5G/L23HfYvoNz/aaLowzKmPKj44H8/ONeG7dcWw9YYoo7ri8Pnx/rBOrSlNPST7kWHPvojz0ubzYUNWBX64oYjUyBLCJtqDfOFDRFmydTP3Bdmt1BEeyTiEJbeaiQeUisspIDi5UrI6RCcmNLPKL9QoJeh2emK4dVHkem03snPFGvL6zAUeaLaEs9eGs3deEdqsTf7tqSmgzMi/POGYxFmcqK0tSkGtU4tFPy+H1+ZFtUGAhQyYbD8+5zpKiJPxrSy0sdveQ626nzYmPD7Tgx9Mz4hZBc6aQrR8QktnS6/AgWcPswlTLxLC7fbQiYK/DgwSGTbtaJkKrhb0DNpojmToojlVINtlcSGR4fVCvK4vdHRchucnsgEwsCBX/MpEgF6OXRZGv0+NDr8ODFI77qWSNLGr+ajSOtVs5mycGi/90YrHZ7mYVlxFyJPfRC+EnTQFT03iG8qr8ZBVEAgIVrVZcNDlylEJ5Sy9++t5BnDT147Jp6fj9paWnNBLiyumZ2N9gxr+DPSUl6Rr84bJSxq8jCAK3zBuHxz4tx+ZqE87LM+KpLwLmtGtn0ecPn0pEQgFeuHYaHlp7GO/tbcSEVA1euHYaK81jYpoWDk896rr6oh6eUfEQ0xmEZEpo3t9gDhOS11V0QCIScC5Vz09SYS9Nod3hJgsUEiFtNMWsXAP+sakG+xrMYY+76VgnpCIBZo+gUHZqVgJk4kB8xmgKyT9Um+D2+iPGWlCcl2eEgAh87mAh2WJ3Y0NlJ66bnUX7N1eaocWmB8/HvvoeCAQEyrJ1nP8+M/UK3LEgF//aHIinuGRKGqeIOY1MjA/unINnvq5CY3c/fndJCa6L8W8snj1H8eD0Vx95hvDrlcU41GTBLz86CgC4c2EuVgdzZU93cgxK2oZYivf2NMHrJ3HdrPg2tp+Xb4REJMA35e1RheQdtV247fV9MKqkeP2WmWE3i1PF6SYiU1w4KQ1Whxe//7oK++rNuGluDh5ZVRx2US5J17IWEoeTopVhalYCvilvx32LI5/qu71+7K7rCRtlOZWUpGmRrJHi2/L2iELyjtpu2FxerCg5N5xPQgGBR1YV45FVxZy+biDPcKiQ7Pb6YXN5ozZ0D3b8soFyLkcSkg1KCavIBjZ5jxQamp+NKw3ddlw0OTXq5+iUEvjJwAabaxZ2U4+d9SZ2dq4eAgLYUNUZUUgmSRLv7GlCSbpmTMulzgbEQgGe+/Ek3Pr6Pvj8JP50+SQ+1oKHh4ElxUl44fsabD5uwiVTB9bHb+1qhMfvP23iJk4leqUEKqmIU+Fer4PdSDN1n+tzeiPeeyx2T+hQlQ6VVASbi/19krqnRvq+IqEACokw9miLPheM6uj3Qmpd0tM/8jJdADhp6kOOQcl6AlEjF4dl20aivTcgzqdwNFykaGXosDo5H0xbnR40mx1Ri9AioR4UR0IrJDN0ZlDolRKIBEToZ49Ek9kOnUIc5uQcjlQkRH6ymrZw74vDrfj5B4dgUErxxi0zGcu3RgOqPPiSqemwOb04vzCRNut3OFeUZeC1HfX4xQeHkW1QoLLNipevLxtzN/JgVFIR/nV9Gfx+klMxIVWcV9FqjSokf3W0HWXZOsYJzrxEFRIUYuyp6x4ycUkGY8cW5Bs5m/ryk9X49FAr+lzh3S2Hm3tRkq6l/fublqWDWEhg98meMCF58/FOzB1vYCymjIZUJMSMHD121o5uTvK3Fe3QKcRRhXydUoJJGQnYUm3CA8sKQu//4kgb3D4/oxYgEQkwd4RGlod+VIhxBiX63V5czxCDEokUrYwxbuZMhN+RnGHIJUJ8dPdcvLJmOj67dx5+vZKbaDOWZBuU6Opz0y7uvD4/3t3TiAUFiciJs4CrlomxpCgJXx4JxFtEorrDhttf34f0BDk+vGvOmInIpzvXzsrCod8sw5EnfoQnLp44KsLGypIUVLRaQyVjwznQaIbd7cN5+WPncBQICKwsScXmalNEIXNdeTtUUhHm5vFiWjSojerwsVZqkxTdkRxYeNGVQA6HcihRkRiD0asCLezD26+Hw+Z5UYQcySMQknv63eh1eJBjiH49ojZfPTE0yTebHcjQKVhtYhMUEiyfmIJ3djdE/L0fae5FVZsVV884PRwtZzpl2XrsfXQp9j66dETuEh6ec4XJGQkwqiTYOKioEgC+PtqGObkGVlmnZxsEQSBLr0ADi3g5CrYZyWpZ9PuclcX34Vq2x5S7HIjKiFVIZnYZU1m95hjut5GoMfUxllEPf3w2GcntwcI8ro7kDJ0cXj/JuXDvh2Ah1kgcyZHw+UlYHJ6oxgIKoYBAskaGtihCcrPZwXpSclK6FoebLPAM2zvuq+/BA+8fwtRMHb65f/6YiMgUBEFg7ngjlk9MYS0iA4FojJevn4ZkjQy1pn48tXriaWt+4SIiAwHhVyoSRM1JPtZuRVWbFReURjdqUI8/PVsflktc3mJFi8WB5THEJVFu49ph8RZurx+VbVZMjlC0RyGXCDEpIwG764YKvSdNfajvtselm2fueCOOd9hgsrGPuel1eFDe0suq2NXu9mJ9ZQdWspjcXVSYhMPNliHXpA/3N6MoRY2JaaNfZiwQELhyRiZunjduTEooT1f438QZiFgowLIJyTFlq4wl44zRR+u21XSh3erEtRxPstly6dR0dPW5sKGqM+xjFrsbt7+xD3KJCG/cOvOUZcueqYiEglE9sV5ZEripf1vRFvHj2050QSggxtzxuKo0FW6vf0ibKxCItVhX0Y7FRUmcFnXnIhpZ5IxkShCNNsZDneCz3YD2BR1Pkcr29AoJPD4SNgZROpaMZCuLEVQ6jgez/OjatymoUdtYcpKbLXZWsRYUt5w3DlZnYAE4nHf3NEIuFmJ1lEZtHm6IR/l6y8NzNiEQEFhanIxNVR2hw666rn7UdPbhR2NcXjyWZBsUaGDpSHa4fXB7/YxOYiB6zwHATpBWyQJle0wHuRTUPZXOMa1mKACMBptoC2pdEmsvwWAcbh+azQ7kcTjgSJCLQ9NR0aCKdKMV9UYiM9iX0MTBwQ4E7v/pCXLOh550k2kUFrsbJMl+rDstQYZWi4P248097Nc8i4qSYHV6sbd+QEDstXtw/3uHkJYgx39ums55Cux0Ii9Jja/vn49Dv1mGNXNyxvrpxA2RUICiFDXKW+hLqF/dVg+5WIjLprGb7J6fb0RDtx21pgHh9+vyNgiD9xyu5AeF5OE5ycfbbXB7/ZhEk49MMXe8AUeae4dchzYFD1DP5xizEYl5QSPUjtouxs/1+Uk8v+EEZj6zARf+cxum/24Dfv7+IdR10R9erq/sgN3tw2qa2JjBXDQ5FSQZmAIAAr+jw02WERUK8owcWiGZIIiTwbdamvfH+lZL95g8ZzfZQUcd3UXl66NtUEtFWFQ0Oqe6i4uSkJ4gx3+3nRyyWHV7/bj3nQNoszjx7xvKxixzl2eATL0CE9M0+Ka8PeLHt9Z0YXKGdtSbZJmYnq1DklqKr48OFby/LW+H2e5hXTh3LqOSiUAQCHPX9PQxZxGHhGTOjuTIZXuDH5cOi8MNiUgAOQthT8Pg1GLDiU52QvLAqG2sjmT2172yLB1SNDJ8Uz70dd/n8uLzw624cFIq48goDw8Pz2hxeVkG+t2+0L35kwPNIAhg2TlWsjeYLIMCzT0O+P3MYi11kMsm7oiKtqBzyPY6PCEHLx1qmQgeHwmXN/LE4HCsTg/EQgIyceRtrFomiklI7nd54fD4YKQpUKag1iVmFmIuE7WmPpAkaLNQI5EQ7ERgghJT0xK47Wuo9QDVn8CG7j4XdtZ24/KyDM7xfHSGAgozh0kwAEjVymkdyX4/iWaLIySWM7GgwAipSICvjgSuJSRJ4uGPDqPD6sQ/r5k65vuQeHE2inET07WoaO2NeEDl95NYV9mOlaUprDtMlhQHxNkNQROFx+fHh/ubsagwMabDhCy9AhKhILTOpzgcjNljcvYvm5AMn58cMn3z5ZE2FKdqOHUT0VGSpkWiWorvKqLHkpIkiSe/qMDfNlQHe5Om4MJJqVhf2YEr/rWDVvf57FAr0rQyzKDpWxlMbqIKUzIT8MbOBnh8fry0uQYKiZAvoB5jojmScwa9DX9/9rCPc33jOQcZZ1RCQISfvAGBi/G6ig4snZA8ag5OkVCAOxbkYm+9OeRK9vtJ/GLtYWyv6cbvLysNawPlGTtWlqTgYKMFLcNcBR1WJ440W7CwYOSnrSNFICBw0eQ0bKzqDC3YSZLEK1tPItugwHl8uRgjQgGBBLkYPf1DR6dCG1kVc7QF64xkF31Gsl7FLhrC0h8oDmKz6B4o24t9s1ndYYNaJkKyhmFjq4xt1Nbm9MBi9yCD5aYKCLzuV5SkYPNx05B4i88PtcLu9p02RS08PDznJtOzdShIVoVK997Z04jFhQEzwblKhk4Bt88PU5QSMgrqQJWNAzRFG3C7Dl+rUVgcbuZoC44FedZgfjPdfTjgSOZ+36UK2piiLeQSIWRiQVyiLSrbAo7JwhT2QrJGLobVGSjXjUaLxQGjSsJ5oiU9BiF547FO+EnE5PpniragsqgNSnbFhqkJMrT3OiMempj6XHB7/awPzxUSES6enIaPDjSj0+bEazvqsa6iA79aWXTGTQafa5SkaWF1eiO+jk909sFi92DuePb7tAydAqXpWnx8oAUkSeLLI60w2VwxR7mJhALkJipR0zFUFzncZIFOIWZ8jZama5GmleHzoEu3rqsfh5osuCROE4ECAYHlE5Ox6VgnHG76qIqXt5zEGzsbcNt54/DCtdOweko6/nj5JHx63zz4SRK3v7Ev7HrcYXXih2oTLpqcxjq25P4l+WjsseOSF7fjs0OtWDMn57QrnzvXiCYkNwJoCP53+Pupj8XyNvz78ZwjyMRCjDMqUdkaPmayvaYLvQ4Pq5yikXDNzCwUJqvxi7WH8eauBtzx5j58frgVD68o5N2jpxkXTw6MGn16sGXI+7852gaSBC6YdHo4i26amwMSwAvf1wAAPjnYgvIWK+5blMc50+tcRa+UhDlpqVGtaI5ksVAAqUjA2ZEcUUhWsHMkm+3uqM9pMGppwG0d64gtEBjfKkhWMwrXIUc1x/IfavPPxZEMBA56XF4/vj8+4IR4Z08DilLUnPMReXh4eOIJQRB4aHkRTpr6MeWp9TDbPbh3cd5YP60xJSOBEgeZ4wq6gwe70Q5yQ99XF3DVDR73pnB5fXB6/KyiLQD2h8JMcRmxOpKpLNBEBkcyEFibxCPa4mCjBWqZCLlGbtEWJAlGsbzF4uDsRgYCRVvJGimaWLxWKH6oNiFFI4spr3Rw2V4kKKMBm7I9AEjTyuH2+dEd4d+nPuiOzGbonRjMXeePh58Elv5lC576shJLi5POydLOMw3qtRipLHFPMFt41jhmN+xgbpiTjeMdNvxnax3+8l01JqRqRpRHXJiixtGWoa7pfQ1mlGXrGNf9BEHgqhlZ+KHahJpOG/7vh1pIRAJcOpVdVAcbLpqUBofHFzZ5S/HxgWb86dtjuGhyWljZ+vhEFV68bhrquvrxwPuHhxzs/G9bHfwkietmsS+uO78wEbfPH4eqNivm5xvxwLL82H4onrhBKySTJJlDkuQ4kiTH0b0/1rfR/7F4TlcmpGlR1RYuJH91JBBrMb9gdB2cEpEAr6yZjkS1FI9/Wo5tNV147IJi3L1w/Kg+Lg93sgwKzBynxwf7mkKuC5IksTYYrh+thfdUkqlX4Ka5OXhndyMeeP8QHvu0HNOzdXG9kZ/tGJRSdA8TcClBlM1ILGtHMptoCyZHsp15TJdCICCgksRe+uPzk6hotaKExcZMLhZCKuLukGruoYRkbmNw03P0MKqk+ORA4KBnf4MZ5S1WXDsr66wckeTh4TmzWDYhGU+tnoiZOXo8d8UkTMs6tyfOuMQVUAe7ehYOUKGAQI5RgZOm8PFltt9HLY0uJA7H6vRCHUVI1shEYQW+bBhwJDML6DqFJC6O5IONZkzJTOBkPKDWIEw5yS0WR8wu/EydgtWhA8WhJgsr8SsScXckB13ybb3hr3VqzJ5Lofr4RBX+e+N0TEzT4sY5OXj+6qn8OucMoDBFDbGQwKGmcCF5d10PUrUyziaK1VPSUJquxTNfV8Fkc+HpSyaOyDQ0PUePTpsLTcG1eKfNibqufsxkKXBfNzsLapkIF7+wHe/uacI1MzLj2vM0c5weuUYl3tjVEBYRsvWECQ9/eARzcg34848nRfw9zB1vxOMXFGNDVQf+vqEaAFDTacOr2+uxeko6sgzs9x4EQeDRCybg+O9W4s1bZ/EdRKcB4bvpQRAEsSb4PzeRJNl8Cp4Pz1lOcaoaXxxuRa/dA21wIUQVky2bOHqxFoPJMijw7f3zcbKrHyla2VmTb3U2ctPcHNzz9gGsq2jHqtJU7KnrQUWrFc9cWjLWT20IDy0vRIfViU8OtmBmjh7/vHYqYwMtzwB6pSTMzWS2u6GRiRjbcVVSEeuyPapITymJIiQzOIx67G5OpTgauTjmsr26rj7Y3T6UpNM3N1MQBAG9krtDitoocl1MCwUErp+dhb9vOIGDjWb8/usqGFUSPq+Mh4fntGHNnJyzqkBqJHCJKxgQgNlN3+QaVagelvMJIHRAzPR9Qo5kTtEW9FvYWKMtTMHny8qRrBSPOCO51+5BdYcNyzlmd1NCcrScZJIk0WpxYHGMpVsZOjn21ptZfW5XnwvNZgfWzGHvLhxMoFBWQBsDxtmRHBTPWy1OTBq2JKnr7odEKODs1J6fn4j5+aPT4cMzOsjEQpSka7FvUFEiEPjb2FPXg7njDZwPBKQiId66dRa+rWhDaXoCJsTgwB/MjJzAAefe+h5kGRTYfbIn+H52QrJRJcUL107Dk19UoChFjV+tLGb+Ig4QBIFbzhuHxz4tx4aqTiwLRtdsO9GFO97Yj7wkFf69piyqfnPj3BxUtFrxj001ONrSi6MtViilQvx6VVFMz4lpX8hz6ogqJAN4DQAJ4FIAvJDMM2Kokef9jT1YXBS4GG2t7oLV6cVFLFo744VIKGAsr+IZe5ZPTEFekgrPfFWFqVkJeOrLSiSppaed21cmFuKFa6fh+atJziUjPIF84r31wx3JblabWKVUNCSnNxp9Ti9UUlHEU3OFJODoZRKSu/pcmMOhkVwti92RfLQl4KIozWAWkoHYHFLNZgfkYiGrUqXh3DgnB2/vbsSlL+0AAPz9qikR3d48PDw8PGOLQiKCXimhzTIeTE+/GyIBEVWsHcz4JCU2VHXA4/MP2eRT91OmiAzKkcrWRWx1ekLCeMTvJxXB5fXD7fVDImIvOphsLhDEQNRVNHQKSSjfOFY2Vwdyhc8v5CZQauWB52eJIiT39Lvh9PhjirYAAtN2Xxxpg9fnZzRGHG6iysFid/0HxH96R7JKKmJtNorqSDb1I9ug4Nfq5wgzcvR4bXs9nB5fKCu8vtuOTpsLM8exX8sPRqsQ46oYc5GHU5Ckhl4pwffHO3F5WQbWVbTDoJSglIWBhGJhQSI2PXh+XJ5PJK6akYnXdtTjVx8dgVg4GbWmfvzpm2PITVTijVtnMhryCILAM5eWIlEtxacHW5BjUOB3l5YgSR0/5zTP2MBL+jynlGlZOkiEAuw6OXA6+OWRViQoxHwxGU8YQgGBP10+CSabC3P+sAmVbVY8tboEigiO0tMBfmEaGwZlQAAdnJ9ltrtZtSCrpKKQ05gJm9NDK3QSBAFDhKzmwbi8PljsHlZuJYqAIzk2IflgowUKiZC1AzpS1jQTzWYHMnTymMY0dUoJ3r19FtbMycY/r5mKS06zAx4eHh4engHSE+SsHck6pYT1fWF8ogpeP4mG7qFRCGydzVS0BduYKqvDG1W8GIhK4Hbv7epzQa+QsJooi0dG8ncVHTCqpJicwa1XgMqHtkQ5OG61OAEgquAejQydHD4/ibZeJ+PnHm6yQCggUJIeuztTLRPB5or87xVYD7KfHtUrJZCKBBGfe313P3I4xFrwnNnMzNHD7fNjf8OAu35LsNtj7vjYhOR4IhAQWFmSgo1Vnei0ObHpWCeWl6ScVlOtYqEAL19fBpGQwE2v7sXTX1Zi9ngD3rtjNmsxWCIS4OEVRdjx6yX48O65KEoZmZOb5/Tg9FRjeM5aZGIhpmQlYOuJLgCBReP6yg5cPCWNH1XgiUhZtg4f3j0HXxxuxfz8RCwo4EfLzjb0Sgn8ZMBdQ204u/vcIVdJNFRSEdqtzBsdIHC9iVS0R6FjEGK7OYy9UmhkYrSycIBFYm+9GVOzElgvKBMUYlZus8E0W+ycYy0Gk5ekxlOrT6+oGR4eHh6ecDJ0clR3hEdQDKe7381pSiU3eNhZa+pDXtLAwSdVdsb0vQaiLZiFX5IkYWUs26Myl70wqNjfr002F+v7u04hRq/DA58/tkk0k82F9ZUduHZWFueMVTbRFi2WgKg/koxkAGgy25Gpj55jerDJgoJk9YhMHhoZfQxYd7+bVV43BUEQSEuQh62H/H4S9d12LIox7oPnzGPOeAMkIgE2VnViXtCwtqGqE3lJqtPmQOGyael4e3cjZj6zEQBw9YzMMX5G4eQlqbDxwfOxs7YbiWopJmdo+ZxwHt6RzHPqWTExBVVtVlS2WvHenkb0u324cvrpd9HkOX2YlJGARy+YwIvIZykD+cSu0PvMdnbRFiouZXsub2jDSvc8ognJoUZ3DhtTTYzRFlanB8faraxz0oCROJK5Fe3x8PDw8Jx5pAfFteGlScNhGy1FkZsYEGSGF+6Z+90QCgjG0WdqUogu2mAwLq8fbp8fGnm0jGT2328wXX0uGFne33XBA/BYJ47e39sIt8+PG2LIFR5wJEcTkoOO5BFEWwBAU0/0wj2SJHG4yYIpmexH8SOhU4hhcURev5j73dCzLDmmSNXK0DZMSG7tdcDt9Z82AiLP6KOUijBvvAHfVbbD7yfRaXVi18nuUNbv6UBZth7Xzw5EZdx23jhM4jihcKpQSUVYNiEZUzITeBGZBwAvJPOMAZdNS4dUJMC97xzA3zecwNzxBkw9x9u0eXjOZSgHUKc1INSSJInufnbRFkouZXvBjGQ6WAvJHKMtormG6NhV2w2SBOvmZiAwatvr8MDr87P6fJvTA4vdMyJHMg8PDw/PmUGGTg6nxx9yCtPBVUjWyMRIVEvDSnO7+93QKcSMjluJSACpSMDqUJgSbqNHW1COZG73Xm6O5MDvh2svAQB4fX68tasR8/ONGM+hvJdCLBRAJRVFdyQH+w8SOAqwFGkJckhEgrDDgeHUdfXD6vSGOnBiJRAVQle2x249OJhIjuS6rsDPMo4Xks8pLp2WgWazAxuPdeKtXQ3wkSSuOs0MbE+vLkHVUyvw2IUTxvqp8PCwhheSeU45CQoJfnvRRNR390MhEeJPl08a66fEw8MzhqRqA0ImFVFhtnvg9vqRrGGOtlBL2TuSbU5P1GgLvTJ65qGpj7uQnKAIFMiwFXcptlSboJQIMT2bmyMZiF7AMxhqk8U7knl4eHjOftKD13qmnOQejtEWADDOoERD91DRsaffxVqQVsvErMr2qAkfTdRoC27lfUDgALvT5kISy/v7wCQVdyH5u8oOtFudWDMnh/PXUmjl4qiO5FaLA+kx9h8Agc6PHIMCtQxC8uHmQNHe5JEKyUr6suCYXo9GJTqsriHrw3peSD4nWVWSgky9HPe+fQD/2FSDlSUpp50rnSAIyCXsyiR5eE4XeCGZZ0y4dlYW9j+2DFt/uYgxe4uHh+fsJkVDNWwHhGQqUziNRUayMtjO7mEh1Pa5vKFSn0gYlBLYXF64vL6IH6ccyUwN9IOhXEtsxV0gsKHdUm3C3Dwjp8Z5yrHDtgCouYcSknlHMg8PD8/ZDnWtb4kiJHt8fvQ6PJwdoMlaGTptriHv6+5zw8Ay21bNMqaKcuFGy0jWxOBItjq8cHv9rA+KqXVAV5+L4TPDeW1HPTJ0ciwuij2rVysXo5cmCgIIHBSnxRhrQZFrVOFkV1/UzzkULAXOT1KP6LF0CjHsbh+cnqHrL4fbB4fHx/n1SGV113YOPP9aU8DAxPawgOfsQCQU4N/XT0eOUYE5uQY8c0npWD8lHp6zArap+D8lCOKSOD0mSZLkrXH6XjxnMFzG5nh4eM5e5BIhtHIx2oNCMiUop7LYBFFRFf0uLxIU0a8pfc7oGclUNmJ3nzviBqyrzwWtXAypiL1rgNr8WOxu1tmLJ7v60Wx24K6F41k/DgDoFdwcUk3mQPYhLyTz8PDwnP2kB6/1zWb63FvKFcrVAZqslqLT6gJJkiEXbIfNyXqqRiUVsSrbowrZNFHu5bFkJHfaAusOtkK1sqlbAAAgAElEQVQy1ZVg6uPmSK5qs2JPXQ8eWVUUU0kfRYKC2ZFckj6y3OLcRCU2VHXA4/PTFqIfbLKgNF07op8FGLxW8iBFO7DG6onx9UgJyTWdfSG3dGWrFUUpaj7f9RxkQpoG3z2wcKyfBg/PWQVbIXlRnB+XF5J5eHh4eEKkamWhaIu2XvaOZNWgDWM0IdnnJ9Hv9kXNSKY2kCabK6KQzCU/kUIXzCfsocn+i8SW4yYAwEKO5ZLU4RxT/iVFczBDkT/U4+Hh4Tn70cjE0MhEUaMtqINIPUsnMUWyRgaHxwebywuNTAySJNFhZR8VoZaJWAm/bKItVDEJyQFncZKaed0BBO63BAF02bg5kt/a1QCpSDDikvEEhRgnOiK7hR1uH7r73UhPYPez0JGfrILXT6K+qx/5yeGO4z6XFxWtVtxzPrdD70gMzpxOGbT2oyasdAxGgeFk6RUQCwnUBHO7/X4SFa29uKIsY8TPlYeHh4eHfbQFEcc3Hh4eHh6eIaRoZSFHcqvFCbGQYOXgpYRhppFY6uPRMpIHC8mRMNlcIRcSW2Ip5NlSbUKuUck59seo5jZq22y2I2MEGYo8PDw8PGcW6TpFWAnZYHr6KCGZm3CXpKFKcwP3cUuw6yCJRdcBEHQkx6lsTywUQC4Wcoq2oBzJ1M/BhEgogE4h4RRt4fX58U15O5ZNSGacoGIiQUGfKUz9+6aPcNqoOFUDAKhss0b8+IEGM3x+klMpMB2htdKwg/Du/thej2KhAPlJahxt7gUQmPTqd/tG7NLm4eHh4QnA1pH8TwAHRvOJ8PDw8PCcu6RqZaEFf1uvA8kaGWPTOzA02iIa1AaVjSN5eM4jhanPhckZ3AplqMZ0C0sh2enxYdfJblw7K4vT4wCAQSmFgINDqtns4GMteHh4eM4hMnTysFK8wYSiBDh0AQAIleN2WF3IS1KjIyjMJrMUZtUyMUtHcjDaQh59C8vW4UzRaaUcyewPi40qbkLynroe9PS7ceGkVNZfQ//YUvT0u+Hzk2GxEgM9EyO7v49PVEEiFKCyzYrVU9LDPr67rhtCAYFpWboRPQ4A6JSBtZJ5WFwHdbDPdRoMAGbk6LB2fzO8Pj/21fcAAKaMsBSQh4eHhycAWyF5I0mSn4/qM+Hh4eHhOWfJNarQ3d8Ec78bdV39yDawc+Mqg8KwjUFIDrmYoozDUqVAUR3JnKMtKEcyO2fU7roeuLx+LOAYawEEWtb1SglMrB3JjrhsAHl4eHh4zgzSE+TYUdM1JMt4MD0xRglQQjLl7O0ICrPJLB3JAeGX+T7Z6/BAJhYwdhWoZSLYXOwdySabC3KxMOph83CMKinteiES3x/vhEQoiOn+PpxElQR+Eujud4XFccTLkSwWCpCfrEJla2RH8p66HpSma0PrsJEQ6ngYdujeEXS4s40cGcz0HD1e39mAyjYrtlSbkKqVhbKTeXh4eHhGBvs6eB4eHh4enlGiICWQv1fVbsXxdhuKUjSsvo6KqmByJFPOpGjRFhKRADqFGKY+Z9jH+l1e2N0+zkKyQiKERCgIG9ek44dqEyQiAWaPM3B6HIrAxpb5saxOD3odHt6RzMPDw3MOkaGTo9/toy1q67S6QoeSXKCcx60WSkgOOpJZCoBUtAVJklE/z+rwRI21oGDrcKbotLmQpJFyinoyqqTo4lC2t6XahFm5eigkIxdeqeivrgj3+/rufkiEAqSO0JEMAKXpWhxussDvH/rv4vT4cLipF7PiEGsBDJTtdQ87CDfZXFDLRJBL2JccU8wZb4BIQODNnQ3YdqILCwsS+SgvHh4enjjBC8k8PDw8PGNOQXLAJbK+sgMurx9FKeHFLpGgnDB9DBtGNrmKQGB8MpLDKDReyTEjmSAI6JRi1hnJW6pNmDVOH9OmCQg+fxaO5JZg2VKGjlsOMw8PDw/PmUtWMHu/nibeot3qRKJKGhaXwIRCIoJRJUVjtx3AQLwC28xhtUwEPwnY3b6on2d1eqJOFg3+flZOQrKTU6wFMLBeYBK/gcDvo7qjj3OJbrTHBiJ3ItSZ+pFlUHD+N4xEWbYOVqc3VFpHsb/BDLfPH5d8ZCDgftYrJWHRYh1WJ2tX+3CMKikunJSKtfubYXN5cc1M7pFhPDw8PDyR4YVkHh4eHp4xJ0Ujg1omwkf7mwGAtSOZbdkeNeIazZEMBMYnqZHcwVCbG2MMOX16pTQ0LhyNFosDNZ0j22gmqqSsMpKbg0Jypp53JPPw8PCcK+QmBg5t67oiC8kdVidStLEJd9kGBRp6At+3vqsf6QlyyMTsDkVVMnb3cqvDCw3DfRwIHBpzK9vjHl2VqpXB4fGxEqx/qDYBQNyEZMqRHOngu767H+OMyrg8zoycgFC8N5gxTLHpWCckIgHmjI9teioSSWppKKuaotPm4izwD+aRVcX4cVkGHllVhMl8PjIPDw9P3OCFZB4eHh6eMYcgCCwuSoLV6YVYSKAghV2OnTLo3GUUkkMFPdGdTClaGdp6wxvtqfelJ3DfYNO5nIcTj42mMehIZnJINZsDrjHekczDw8Nz7pClDzhVT5oiC8ltvU6kxOgAzTYo0BB0JNd125FjZH9/UQenhZjiKHodHmhZOpK5RFuYrOFZw0xQTtn23vA4rOFsqTYhLY4ZvUYaR7LPT6K+2x43ITnboECKRhZanwAASZLYWNWBObmGuMR0UATWSkN/lyNxJANAkkaG5348GXcsGD/Sp8fDw8PDMwheSObh4eHhOS24d1EeAODJi0sYi3QoREIB5GIh62gLJkdyWoIcnTYXPD7/kPdTDt60BO4O3kSWhTzfH+sc8UYzUSWF2+tnLB9sNjugkAihUzBvyHl4eHh4zg4kIgEydXJ6R3LvCBzJeiXaep1wenyoM/VxEjPVVHEug4uYS7QFW0eyw+2DzeWNyZEMBOJAouHzk9he04X5+fHL6FVKhJCJBWFri1aLA26vP25CMkEQWDYhGVuqTXAEY0cONllQ323HqtKUuDwGRZJaNuTnIUlyxI5kHh4eHp7RgY2QzKfS8/Dw8PCMOgXJapQ/uRzXzuKWY6eSidDvZnYkS0XMTe9pWhlIcqAoiKLZ7IBBKYnJfZPIwiXcYXVi07FOrCxNHdFGk9oIMwnXzWY7MnRyvniGh4eH5xwjN1GF2mGZt0CgVNbm8sbsAKUcyPvqzbA6vRhnZH8oSkVbMLmIzf1uJLASksVwevxhh8KR6Ay6YLkKlgOO5PAppsGUt/TC6vRiXr6R0/ePBkEQSNbI0DHsXk9lX8dLSAaAFf/f3p3HyXWVB97/Pa1eJPWi1tLaLdmWvAsbG2NjGwMxizGEJQQCYYvZYRiIw0wyb5LJxJm8L0zCCyFAhgABjP0mhB3yBowJOAa8BGObxRteZGuxtVhbq6WWWmqpz/xxb3WXWlXV1d1V6u33/Xzup2/VPXXrtKSjU/Xc5z5n3VL6+ge48b6tAPzTTzcxp2kWLz13ec3eA7J62sWflXb1HubwkYExX9iQJNXPSIHkU/Lt305AXyRJM1yh5vFoXzPSl8+evv7BW2crKWQcF1aeLygEXsdiUVsz/UcTew+Wz476wm0bOJoSb75k9ZjeY+i9Ciu5jxRIPmhZC0magU5d1MqGXb0MDBx7cXNrXqJh6byxZYBemNfT/fSP1wNUvWguMBgcrjRPHh1I9PQdoXNu84jna68yMA1DayAsHmUAfSiQXHm+vfXRnQBcWsN6wgDL583hybxMVUEh07yWgeRLTl3IaYvb+NQt67lrw26+cc8TvO6ik8b0ea2Sxe0t9B9N7DmQ/RsYXMvBzyqSNOlUDCSnlDbmW+VLrZIkTZC2lkZ6R1qgp6+6BXqW5zWQh9dJfrL7ICvGGEiutLo6wK79h/ji7Rt4+XnLWb1wfF/+BjOSy7xXQRZIdqE9SZppTulqpa9/gK3D7rzZnAclxxq4W9E5h1UL5vKTR3bS2jxrcKG2aszLyyx1Hyi/MG2hRFVnFSWZOgZrLo9c3qJQ43i0taGbGxtY1NbMtp7KX5Nve3QnZy3rGLzQWysr5s857qL3Yzt6mds8q6blIBoagj9+yZk8umM/r/77O+hqb+F9V5xWs/MXDK85vXl3/u9xgYFkSZpsrJEsSZrSWltmVbXYXnsVt8Mum5cFVwuZMAADA4kn9xxkxRjqI8NQcPepMlnC//7QDg72H+Udl586pvMXW9SWZWpVykju6etn78F+A8mSNAOdmpeceGxYeYtC4G7VOAJ3V+V1c3/jzMU0N1b/NbNzTjZ3dR8oH/jdkweZ59c4I7lw4XjZGBbTXdE555jPC8P19R/lro17uKzG2ciQ3UG1fV8fh48Mle/YsKuXkxe21rxs1RVnLuELVz+T9z//NL7+nktZ0Dry38FoFf7dbdqdZVVvHlwU2M8qkjTZ1PaeFEmSTrC2liae7K6cEdRzsL+qjOTWlkYWtbWwcdfQQkRPdh/k0JEBTu0a2yJ4i0eoW3z7oztZ0NrM2cs6xnT+YvPnNjOrISpmJBeCBZa2kKSZZ01XdufLYzt6ufy0rsHnN+46wOymhlEvOlfsj648kxectYRTR1laobmxgdbmWYNlDUrpzjOS51WRkVwoZdVTRUbylu4+2loaB7OYR2Plgrnc/+Tessfv2rCHw0cGalofefC9O+cMrulQyNpdv2M/567srPl7ATzvjMU874zFdTk3wKqF2e+wYVf2GWXz7oMsaG2mtcYlNCRJ42dGsiRpSmtrmcX+Q5W/LO7r66/6S+KpXa08tmMokPxonrW1dvHYAslL55WuuwzZquS3rd/JJWsW0tAw/gyihoZgYWszO/eVvz14Y/4l7eRxltGQJE09Xe0ttLc08uhTx2Ykb9p9gFUL5o4rm3VWQ/DMkxewcAxlHDrnNtN9sPzc1V3HjORlY1zQbdWCuTyx5yBHB0ovpnvroztpmhVcNIoyH9UqlNsqZET39PWzeffBmlyUnggds5tY2No8eCF/8+4DnGQ2siRNSgaSJUlTWtvsRvaPuNjekcEvliNZ09XKYzuHAsnr8y/ba8eYkdzW0kjn3CaeGLYoDsD6Hb1s7znEZWtql63U1d4yuAp9KYXFeFYvNCNZkmaaiOCsZR3cv+XYTNpNuw6wasHEXWCc39pUsbRF4VhnFWWqhmokVxNI7mPZGEtXrVowlyMD6bh1FQpue3Qn56+aX5es2kIpiMKc/uCWHoApG0iGLCt5464DpJR4cGsPZ4xiwUZJ0oljIFmSNKW1tTTRe+hoxTb7+vrpqOLLJ2Srne/uPTyY/bR+x34WtDYzfxw1AVfOn1Oy/Mbt67PV3C9bW7v6iUs7ZrOtp3xpi427eulqb/F2UUmaoc5Z0cEDW3sGM2n7jw7w+M7ewbIXE6FzTvNgHeRSCmUvqllsbygjubrSFstGudBeQSGYu3n38fP7nt7D3Ldlb00vFBdb0TmHtpZGHtqWBZAf2Jr9PGf51A0kn7KwlUef2s/WvX3s6j3MuhXzJrpLkqQSDCRLkqa0tpZZHD46wKEjpYPJh48M0Nc/QHuVgdNCCYuHtu0D4P4tPZy+ZGzZyAXlFuS59ZGdgyvd18rSebPLZkdBVn/wFMtaSNKMtW75PPr6BwYX3Htk+34OHx3gnAkM3HXObWJvhYzkvQcOE0FVZaraZzcSUXnxPoBDR46yc/+hMS20B8dnBRe747FdpATPPq32C+1BVsrqjKXtPLg1+6zyi83ddLW3jKvG9UQ7f/V8ntp3iO/euxWAc5YbSJakychAsiRpSitkGvccLH0LayEjqdrSFuflC9X8fHM3Bw4f4f4tPTxj9fxx9XHl/Lk8sSe7XbOg/+gAd6zfxXNOX1TTFdaXd86h+0A/Bw+XDqxv3NVrWQtJmsHOOymb5+7auAeA+/IyF+smMJt1/tzKGcndB/uZN6epqvUEGmc10DG7qeL5ALbvze7eWT5vbKUtVnTOYW7zLB7evu+4Y7c+upO2lsa6LX4HcObSdh7c1sPAQOK2R3dy6ZqFNf08caJdcmoWdP/gdx+kubGBs5ZZ2kKSJiMDyZKkKW1eHkjeW2aRnkKNxGpLWyxsa+GURa3cvXEPv3piL0cHEhesGm8geQ59/QPs2D9UcuIXm7vZd+gIzzmta1znHq6waNCWElnJBw4fYXvPIU5eZEayJM1Ua7paWdLRwq2PZOWV7n1iL63NsyZ0EdbOuU3sPdjPQJmF6/Yc6K9qob2CBa3Ng+UwyincvTPWjOSGhuC0Je2DdzAVDAwkfvDAdp69dhFNs+r3dfv8VfPZ13eEL/1sEzv3H+bZa+tTRuNEWdPVyvJ5sxlI8FtPX8HcZktwSdJkZCBZkjSldeZfLMvdwtozmJFcXSAZ4Bmr53Pn47u58d6tzGqIcQeSz1iSZdUUf9n88cM7aAi4tMZf/JblmVVbu49fcG/T7mzBPzOSJWnmigievbaL29bv5NCRo9z866d41qkLq8r2rZfOuc0MpPIL5HUfODx44bi68zWxp7dyRvLWvdk8uWyMGckAZy5p56Ht+4654+gXT3Tz1L5DXLluyZjPW40rz1lCS2MDf/rN+5jd1MDzzlhc1/ert4jghrdfzGuesZL3PX/tRHdHklSGgWRJ0pRWWMG9XCB5MCO5ytIWAL99wUr2Huzni3ds5MpzloxroT2As/JV1B/MF8OBLJD89JM6R/XFuBrLO8tnJG/I6zhOZNaZJGni/eZ5y+g+0M+ffes+nuw+yFVPWzah/ZmfL6JXrhxF94H+wTbVna9yqQwYmieXjzEjGeDMZe3s7j3Mtp6hi7c33b+NxobgijPqG0hun93E2y8/hQh413PWTOn6yAVrutr48GvOY+V8L3hL0mRlIFmSNKUVVnDvPlgukDz6jORnnbqAF569hLWL23jfFaeNu4/zW5tZNm82D2zJAsk79x/iV0/u5Tmn17asBWSL7TUEJRf327Ary0heZUayJM1ozzu9i7OWdfCVu55gacdsXnROfYOeIxlpLu8+eHjwDqRqzJ/bPHJGcncf8+Y0jauEwjNPXgDATx/bDUBKie/fv51L1ixk3igC32P1h1eeyb3XXsk1Lxj/ZxVJkqph4SFJ0pTWOadQ2qL0F8bCInwdc6qf8iKCz775wvF3rsg5yzv4+eZuUkr8/7/cQkpw1braZ4C1NM5ieeecwezjYo/t2M+ituaqVr2XJE1fEcH1b72IG/5jIy8/b9mEzwuFIHHZjOTe/sFgczXmz22qqkZyYV2BsTprWQcdsxu5Y/0uXnn+Cn75xF4e39nL2y8/ZVznHY22Fr/SS5JOHDOSJUlTWvvsRiJgb5ksprHUSK6H3zhzMRt3HeDBrfv48s82c/ayDs5YWp8VyU9Z1MqGXccHkh/ato/Tl7gKuiQJutpb+MALT2ft4omfF+bPLX9RuP/oAPsOHRm8cFzV+VqbOdh/lL7+o2XbbNx1gJMWjO8OnVkNwWVrF/HDX2/n0JGjfOG2x2lraeTl5y0f13klSZqsDCRLkqa0hoZg3pymCovtZRnJE52x86Kzl9IQ8JKP/4Rfb9tX12yl1Qvn8vjO3mMW/xkYSDy8fT9nLu2o2/tKkjQWldY76MkvFM9vHV2NZCif4TwwkNi0+wCrxxlIBnjDxavZuf8wb/nCz/j2L7bwxmetnvCL15Ik1cuUCyRHxKyIWBcRV0fEJyLijog4EBEp366t0/u2RsQHIuK2iHgqIvoiYmNEfDkirqzHe0qSqtM5p6lsXcWeg/20z25k1gSuRg9Z5tc1LzgdgCvOXMwrn76ibu918sJW9vUdOea23k27D3Cw/yhn1ikLWpKkseqY00QEJctRFJ4bzeK0C/JFcnftLx1IfmrfIQ4dGWB1DdYMuGztQp5/5mJuX7+Ls5Z18PvPt16xJGn6mooFlb4CvOpEvmFEnA98DTh12KFV+fY7EfFPwFtSSpVXdZAk1dy8uc1layR3Hzg8mJk00d53xVpe+fQVnLRgDhH1C2yvWdwGZKUsLlmzEIAHtmYL/Z25zECyJGlymdUQdMxuYm+JuXzvwey50Sy219XeAsCOfYdKHt+Yl39atbB1tF09TkTwmTdfyC82d3Puynk0zZpyuVqSJFVtKs5ys4Y93g08Uq83i4jVwI0MBZHvBN4PvB74ELArf/71wOfq1Q9JUnmdc5rK1kjec6Cf+Sdg5fRqRASrFs6taxAZYN3yeQDcv2Xv4HP3bNxDS2ODpS0kSZNSuQXydvf2Dx6v1uI8kPzUvr6SxzftPgBQk9IWkAXCn7F6vkFkSdK0NxVnujuB/wW8Bjg1pbQQ+GAd3+9jwJJ8//PAJSmlT6SUvpRS+hPgAmBTfvyNEfHSOvZFklRC59zyNZK7DxweVRbTdNDV3sKSjhbu39Iz+Nw9m/bwtBXzaG6cilO/JGm665zbXLKm8c79WVZxIcu4GoW2T/WUzkjetPsAsxqCFfPnjKGnkiTNXFPu22RK6YMppT9OKX0tpfR4Pd8rIs4DXpk/3AS8N6U0MKw/m4D3FD11bT37JEk6XuecprKlLfYc6KdzkmQkn0jrls/j3iezjOSDh49y35M9XLB6/gT3SpKk0ha1tZQsRVF4bmFr9YHk2U2zmDeniafKlrY4wPLO2WYQS5I0Ss6clb22aP8zKaXS90ZlpS8ezfcvjIg19e2WJKnYvLnN9PQd4ehAOu7YnklUI/lEuuiUBTz61H6e7D7ITx7ZweGjAzz39K6J7pYkSSUt7mgZzD4utnP/ITrnNo36jpqu9tKBaYCNuw+wqkZlLSRJmkkMJFf2oqL975VrlFJKwE1FT11Ztx5Jko7Tma/k3jOsTvKRowPs6zsyIzOSn3/WYgBufnA7N963jY7ZjVx0yoIJ7pUkSaV1tbWwq/cwR44ecwMoO/Ydoqut+mzkgsXtLeVrJO/qZdWC8S+0J0nSTGMguYyIaADOyh8eAX45wkvuKtpfV5dOSZJKKgSKu4cFkgsL8M3EjOQ1XW2csaSdP/v2/Xzz50/yqgtWeguvJGnS6mpvISXY1Xtsqaod+w6Nqj5yweL2FraXqJHc09fPngP9rF5oRrIkSaPlN8ryVgKFTxdPppSOjNB+Y9H+6fXpkiSplMFA8rA6yYXV32diRnJE8JevXJctJtQ5h/c//7SJ7pIkSWUVgsXDy1Hs3H+IRWPISF7eOYftPX3HZTg/vqMXgJMXmpEsSdJoNU50ByaxzqL9nVW031XmtZKkOps3J8s4Hp6RXAgsz8SMZMjqJN/zZy+kraWRWQ0x0d2RJKmsxXkgOStHMW/w+bFmJJ+0YC5HBhLbevpYOX8o+/jh7fsAOH1J2/g6LEnSDGRGcnnFnyzKLbJX7GDRfnu5RhHxzoi4KyLu2rFjx5g7J0kaUsg43nvg2EByIatpLJlM08W8OU0GkSVJk16pjOR9ff30Hj46GGQejZPy4PETew4e8/wjT+2nubGB1WYkS5I0agaSq5NqdqKUPpNSujCldGFXV1etTitJM1phsb3hpS229WTXAZfOm33C+yRJkqrX1d5CBGzpHsrhebI7CwKvmD9n1Odbmb/muEDy9n2s6WrzIqskSWNgILm8/UX71XxyKW6zr8Z9kSRVMG9OExGwe1hG8vaeQzTNCubPwBrJkiRNJS2Ns1jSPnsweAzwZB4EXtE5+kDy8s45RMDm3QeOef6hbfssayFJ0hgZSC6vu2h/YRXti9t0l20lSaq5xlkNLGxtZse+YysRbe/pY3H7bCLMOpIkabJbOX8OT+wZCvwWsonHkpHc3NjA8nlz2LCrd/C5HfsOsWVvH09bMa/CKyVJUjkGkst7Aih8ilkZESMtTLi6aP/h+nRJklTO4vbZbO85dqX3bXv7LGshSdIUsXL+HDbvLspI7j5Ic2MDi1rHttbBWcvaeWBLz+DjXz2R5fucu9K10SVJGgsDyWWklAaAB/OHjcB5I7zkwqL9++rSKUlSWUs6WvKV3ods39fHko6Zu9CeJElTyUkL5rKtp48jRweArLTFis45NIyxnvHZy+exfsd+Dh4+CsDdG/fQELBuRUfN+ixJ0kxiILmym4r2ryzXKLJ7pouP31SurSSpPpZ0HJuRnFJi+94+lnSYkSxJ0lSwcv4cjg4ktu7NLgw/trOXVQvmjvl8Zy/rYCDBr7f1sLv3MDf8x0aee3oXc5tHutlUkiSVYiC5sq8U7b8rIspFI64C1ub7d6WU1te3W5Kk4Ra3t7Bz/6HBLKb1O/bTe/goZy5tn+CeSZKkaqxdnC2C99C2ffQfHeDRp/Zx5rKxz+Pnr8pKWNz6yE4+fNNDHDh8lD95yVk16askSTPRjA0kR8R1EZHy7dpSbVJKvwS+lT9cBXwyIo75M4uIVcCnip4qeS5JUn0t7phNSrCr9zAAdz6+B4BnnrxgIrslSZKqdMbSDiLgga09PLajl/6jibOWjr0MxZKO2Vx08gI+8m8P86U7N3H1pSdz2hIvMEuSNFZT7p6eiDgFeNuwp88t2r+ixMJ4X08p/XyMb3kNcAmwJH/fdRFxA7ALeBrwLmBh3vYfU0rfGeP7SJLGYWlewmJL90GWdMzmZxt2s6itmVMWtU5wzyRJUjXaWho5eWErD2zpYfXCrKTFeDKSAd7wrFXcuWE3C1ub+f0XnFaLbkqSNGNNuUAysBr40wrHL8+3Yo8CYwokp5Q2RsRVwNeAU4GL8224fwLeOpb3kCSN38l5wPjxnb2cv2o+dz6+m2eevICsjL0kSZoKzl7ewd0b9tA+u5HW5lmcuqhtXOd7xdNXcNridlqaGuiY3VSjXkqSNDPN2NIWo5FnM58L/BfgDmAncAjYDHwVuCql9IaU0uGJ66UkzWyrF86lsSFYv2M/W7oP8mT3QS60rIUkSVPKlecsZVtPH1+9+wleePYSmhvH/5X17OUdrOkaX0BakiRNwYzklNItwLjTy1JKVwNXj6J9L/DRfJMkTTJNsxpYtVTQXgcAABmySURBVHAu65/q5WcbdgNwkYFkSZKmlCvPWcKitmwB3dddtGqiuyNJkopMuUCyJEnlrOlqY/2O/fxsw25am2dx1jjrKkqSpBOrpXEW33n/swmyhXQlSdLkYSBZkjRtrFs+jx8+uJ3dvYe5YPV8GmdZwUmSpKlmiQFkSZImJb9hS5KmjRevW8pAgl29hy1rIUmSJElSDZmRLEmaNk5f0sb5qzrZ33eEV1+4cqK7I0mSJEnStGEgWZI0bUQE33jPpUSMe01WSZIkSZJUxNIWkqRpxSCyJEmSJEm1ZyBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkWRUproPsxYEbEPeGii+yFNU4uAnRPdCWmacnxJ9eP4kurH8SXVj+NLqp8zUkrtE90JgMaJ7sAM91BK6cKJ7oQ0HUXEXY4vqT4cX1L9OL6k+nF8SfXj+JLqJyLumug+FFjaQpIkSZIkSZJUkYFkSZIkSZIkSVJFBpIn1mcmugPSNOb4kurH8SXVj+NLqh/Hl1Q/ji+pfibN+HKxPUmSJEmSJElSRWYkS5IkSZIkSZIqMpAsSZIkSZIkSarIQHIZETErItZFxNUR8YmIuCMiDkREyrdrqzzPdUWvGXEbRf8uiYjPR8T6vF+7I+LuiPjvEbFozL+4dAJMxvEVEdeO5lwRcXIN/iikmqvV+Cpx3nMj4q8j4ucRsSMiDkXEExHx04j4aERcVeV5nL80ZU3G8eX8pemiFuMrf+1oxkNhu6WKc6/L+/XriNgfEXsj4t6I+FBErK7Fn4FUL5NxfI3hfM+r8R+LVBO1/nwYEWsj4q/yz4G7I6I/Inry+eeGiHjJKM/34oj4ckRsjIi+iHgqIm6LiD+IiNZR/bJA42hfMIN8BXjVRHdiuIgI4CPANUAUHZoDzAcuAP5zRLw+pXTzBHRRqsakHF/SNFHT8RURc4GPAu/g+AvQK/LtIuCtQGeF8zh/aTqYlONLmiYm8vPhY5UORsR/BT4INA07tC7f3hsR70wp/XOd+ieN16QdX9I0ULPxFRH/F/A/OX6+aQfOyLc3RsTNwGtSSrsrnKsF+ALwu8MOdeXbpWTz16tSSr+qto8GksubNezxbmAXcNo4zvku4KlxvB7gQ8Af5Pu9wOeAO4E24LeBFwJLgG9HxOUppV+M8/2kepis46vgz4D7RmhTq/eSaq1m4ysi2oB/BZ6bP/UU8HXgHqAHWAasIpt7ThrhdM5fmg4m6/gqcP7SVFaL8XUz8FtVtGsA/j+yi5mQfdEuKSLeDXw4f9gP3AD8iOxL/pXAq8m+4N8QEd0ppe+Nor/SiTIpx1eRT+Tnr2Sk+U2aKDX5fBgR15B9Zyr4MfAdYDNZ4s35wJuAFuAK4DsR8eyU0tEyp/wi8Np8fxfwGeBeYBHwRrJkhTXA9yLi4pTS5mr6aSC5vDuBB4G7gbtTSo9HxNVU959gOd9PKW0Y64sj4nzgj/KHe4HnDLtq8Ok8Zf7Pyb6Yfyb/x1B1yQzpBJl042uYW1NKt9ToXNKJVsvx9fcMBbluAN6bUtpXqmFErCx3EucvTSOTbnwN4/ylqWzc4yultAnYNFK7iHgxQ0GuR1JKPynTbhnZ3TQAR4CXpJR+UNTkc0V9bCSbv05PKfVV22fpBJl042uYe1JK36q2L9IkM+7xld+l9pdFT70tpfT5Eu0+CPyE7K61ZwEvA44bOxHxCoaCyJuAy/MxXDj+d8A/AG8hS174KPCaavpqILmMlNIHJ7oPJfwPhm4H/pMyqed/AVxFdmXhmcBLyK5gSJPGJB1f0rRQq/GVfwl4Q/7wRuD3KgV2U0pPVDid85emhUk6vqRp4QR/Pnxr0X6lL/p/BMzN9/9mWBAZgJTSdXm9yteQ3T3wNuDvatVRqRYm6fiSpoUaja9LyRJqAH5WKoicv9fjEfG/yLL4AS6nRCAZuLZo/z3FQeT8PAMR8V7g+WR3wL06ItallEbM/HexvSkiItrJvmBDdrvjdaXa5V9CPlH01GtLtZMkaQR/mP8cAN431uxg5y+ppJqML0mjFxELgJfnD48C15dpFwxlZw2fo4b7eNG+85dmrGrHl6TjLC7af2SEtg8X7R+3WF5EnAY8vXCulNJ3S50kpXQQ+GzRU79TRT8NJE8hzyWrgwLw45TSgQptbyraL7vKtyRJpeSrz/9G/vCWlNL6cZzO+UsqUuPxJWn03sDQvPT9lNKTZdqdQ3brMMD9I9SOvJ3sYinAZflFVGkmqnZ8STrW9qL9kWorFx9/sMTxK4v2bypxvFhxXf8Xj9AWMJB8on02IjZFxKGI6I6IByLisxHxnCpeu65o/+5KDVNKO4CN+cNFEbG4UntpmhjP+Bruf0bE+ojoi4ieiHgkIm6IiJfl2SnSdHc5Q6UobgaIiNdFxPcjYns+Np6IiG9ExKtHGBfOX9Kxajm+hnP+kkb2lqL9krcO50Yzfw0AP88fNgBnja1r0pRX7fga7j9FxK8j4kBE9EbEhoj4akS8ISIsyaqZ4DZgZ77/zIh4S6lGEXEy8Mf5w11kC1sOV/X8BfyC7O4BgLOr+bxoIPnEegFZ3axmYB7ZB4y3Az+KiH/NbwMp5/Si/Q1VvNfGov3Ty7aSpo/xjK/hLgdOJbua3g6sJVvV9F+AO/JsMmk6u7Bof0NEfBf4EvBCstuuWsiytH4L+Cpwc4Ux5vwlHauW42s45y+pgog4j2zVe8i+sP9LhebOX9IojHJ8DfdM4AyyRfrmAquBV5MFye6LiHNr2FVp0skXaX032cKuAJ+PiB9FxB/mCQfviYjPAr8m+5z4JNkCsLtKnK7q+SuldCQ/F2RlMlZUaA642N6Jsg/4N7KVHDeTRftXAi/KN4CXkgW8Lksp9ZQ4R2fR/s4Sx4cr/sfUWbaVNPXVYnwV9AH/DtwBPA4cBpaS3Zr/CmAWcDFwe0Rc5K1amsaWFu1fSxaMOgR8kexq+VGyYNjbyRaFeB5wY0RcnlI6POxczl/SsWo5vgqcv6TqFC8C9o8VxhQ4f0mjNZrxVXCEbO77MfAocADoIlt47NXAbLIA860R8ewyCzZL00JK6ev5gsyfIEuMe06+FesF/hT4Qkppd5lTjWX+WlX02oqLPBtIrr9PAO9NKfWWOPaRiLgc+BpZBso64CPAO0q0bSva76vifQ8W7VujS9NVrcYXebuPl/nP+OMRcQ7ZaqhrgeVkC4a9cHzdlyat4g8fa4E9wPNTSj8vev4fI+KTwI/IrlxfBFwD/PWwczl/Sceq5fgC5y+pKhHRTFa/tWCk2+6dv6QqjWF8AdwKrE4pbSlx7FMR8SfA18mylduBL0fEupTS0RLtpeni34H3A38LnF3ieCvwAWBWRHy4zILNdZ2/LG1RZymlu8sEuQrHfwK8imwlYIC3RMRIqeSu7C1R2/GVUrqvwhU9Ukr3kxWfL/wn+4KIuHhsPZcmveGfD/7bsCAXAPkiYe8ueur9I5zX+Uuq8fhy/pKq9nJgYb5/9ygzG52/pMpGPb5SSo+WCSIXjm8mW3x5W/7UmWRZytK0FBFdwC1kd1x3Ae8lK/PSnD/+beCXZIkBfwXcEBEjxXVrPn8ZSJ4EUkq3Ad/PH87i2BUWC/YX7c+p4rTFbfaNsWvSlFfl+Kr2XOuB64ueeuk4uiZNZsXzRh9wQ4W232GortaKiBi+wJDzl3SsWo6vqjh/ScCxt91Xky3p/CVVb7Tjqyp5/de/LXrK+UvTUkS0kmXpX05WauLilNL/TiltSin1p5R2ppS+ATyLrJQZZHcBvKfE6eo6fxlInjxuKdo/o8Tx7qL9hSWOD1fcprtsK2lmuKVov9T4mqhzSZNV8bzxYL74Q0n57VTF2ZRrKpzL+Uuq7fgajVuK9p2/NKNExHKG1s7oA/6pipc5f0lVGOP4Go1bivadvzRdvZehRfI+nFJ6vFSj/HPjB4qeel+JZnWdvwwkTx7FizPML3H84aL9k6s4X/Gq3A+XbSXNDCONr4k6lzRZPVS0v7eK9sVt5g075vwlHauW42s0nL80k/0e2Z1pAN9MKVUT6HX+kqozlvE1Gs5fmgmKs+1/MELbnzKUdXxGRIz5+1dENJKtxwHZQn4jLshsIHnyGOkKwH1F+xdWOlFeV6XwQWZnSumpcfZNmupqmSFitolmguK6dh1VtC/+8DI8MOb8JR2rluNrNJy/NJNdXbRf7W33o5m/GoDz84cDwINV90ya+q4u2q9ZWYsizl+aCZYX7fdUapjfsVbcZu6wJlXPX8DTGboQ9ECZxfuOYSB58nhu0X6pK9i3AIfy/edERKU6J8U1YG8cZ7+k6WCk8TVR55Imqx+RXZEGODsiZpdrGBHB0JdnOH5c3ILzl1SsluNrNJy/NCNFxLMZul14I/DDKl96P/BEvn9ORKys0PZShi4M3ZZSskayZoRxjK/RcP7STFAcGD6pUsP8+1RX0VPDF12+qWh/pDWiXly0/70R2gIGkieFiLiUob/cAY79SwcgpbQf+G7+sINjr/oVnyuA/1z01Jdr1lFpCqpmfI3iXGvIbt0q+G65ttJUllI6CPxL/nA28KYKzV/K0O1Qj6eUjvmA7/wlHauW46tazl+a4d5StH9dNdlWMJjx9dX8YVC6DmXB+4v2nb80k4xpfFUrIhYAv1/0lPOXpqviLOLXjdD2t4GmfP/elNKh4oMppUcYWmPjtIi4qtRJ8mSGdxQ99ZVqOmoguY4i4s0R8cL8y3G5Ns8Gvkn24QTg+pTS5jLN/xIo/Mf8oYg4t0Sb/wFcnO//DP+j1TRVy/EVES+LiFdHxKzhx4ranEN2ha6QTXlLSun2sf8G0qT3F8CRfP+vIuLpwxtExKnAp4qe+nCZczl/Sceqyfhy/pIqi4hW4Hfyhwm4bpSn+DBwIN//QEQ8v8R7XA28Jn+4GfjcqDsqTUHjGV8RcUlEvD0iWiq0WUl2h9qy/KlHqDLQJU1BXyraf1tEvLFUo4g4D/hY0VM3lDnfXxTtfyoiVg07TwPwd0Dh+a+llIqD2WU1VtNoJoqIU4C3DXu6+IvvFXlR6mJfTykVr6x9AdnVs80RcRNwL7ADOAqsJFvZ9EUMBbnuB/6gXJ9SSj+PiL8G/htZvbzbI+IfgDuBNrKrEoXVUvcD76z1FUGpFibh+FoD/A2wIyK+B/wC2Ab0A0uA5wGvYOj/zC0cm9klTRo1Gl+klB6KiD8F/opsYZP/iIjrgNvIxtmFZFew2/KX3AR8ulSfnL80XUzC8eX8pWmjVuNrmNcwNI5uTiltGE2fUkpbI+K/kF3UaQRujIjryUrUNAJXAa/Omx8hm7/6RvMe0okwCcfXEuCzwEfy73J3ky3y1UdWE/kysrFVuAi6H3htSulIiXNJE6oW4yul9L2I+BbwSrKk3xsi4k3AvwJbye7sfC7wWqBwAeaXwCdL9Sml9O2I+HLefjVwd0R8mizzeSHwZuCivPlW4ANV/8IpJbcSG9kH7zTK7eph5/jYKF77DWBhFf0K4KNkt+iXO9d24IqJ/jN0cyu3TbbxBVwzinP9GFg90X+Gbm7ltlqMr2Hn+2Pg8Aiv/yowd4R+OX+5Tfltso0v5y+36bTVenzl5/xxUdvXj6Nv/3WEsdoDvG6i/wzd3Mptk218kQXLqu3HvcC5E/1n6OZWbqvV+CK7cHJDla+/GVg6Qr9ayDKdK53nUeC80fy+ZiTX14fJrqw9iyx7cgmwiKwe3l7gceB2stvt76nmhCn71/CBiPgq8E7gOWSrO/YBjwHfAj6VUtpZ219FmnRqOb5uILsCfglZFtjy/FytZF8MNgP/AfxzSumWWv8i0mSWUvpQRHybbM55EVnGfxNZ1uNtwOdTSjdXcR7nL2mYGowv5y+pjIhYC1yeP9xLllgwJiml/zfP+n838EKy2uUDwCbgO8D/TiltHF+PpamjBuPrB2R3zFxClhW5kmz+6iDLPt5Kdufa14HvpJQGatBtaVJL2Toab4qIT5DdQXYpcDLQDhwku7Psp2TB4e/l368qne8Q8LsR8UXgrWSxk8XAPrJSMV8FPpNS6i1/luPFCO8rSZIkSZIkSZrhXGxPkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRpFCLieRGR8u3aie6PJEmSdCIYSJYkSdK0URTgLWyfGMVr/3b46+vZ14kQEddExLURcc1E90WSJElTi4FkSZIkTWe/GxHNIzWKiCbgd09AfybaNcCf5z8lSZKkqjVOdAckSZKkOjhC9ll3IfAy4OsjtP9NoGvYa0tKKd0CxPi7KEmSJE0dZiRLkiRpOloPPJzvX11F+0Kbh/PXSpIkSSpiIFmSJEnT1fX5zxdHxJJyjSKiC7gqf/jFuvdKkiRJmoIMJEuSJGm6uh4YICtT8YYK7d4INOVtr6/QDoCIeF7RgnzXlmmzIT++IX/cGBHvjIhbI2JnRByMiEci4pMRsbLCe51c9F7XjdCvsm0L/QFW50+tLrEwYYqIq8ucuzki3hYR/xIRmyOiLyK6I+JXEfGRiDi5Ut8kSZI09RlIliRJ0rSUUtoM3Jw/vLpC09/Lf/4wpfRErfsREYuAW4BPA5eR1W2eDawF3gv8KiKeUev3rZWIuBD4NfAPZPWmVwItwDzgacAHgIci4l0T1klJkiTVnYvtSZIkaTq7DngB8LSIuCCldE/xwYg4HzivqG2tNZIt9HcZ8O/At4CtwArg7cA5wHzgnyPinJTS4Tr0AeCdwFzgM2SLCu7Inxtu+J/PJcAP8tcC/BC4EdhMFgy/BHhzfvzvI+JQSum6OvRfkiRJE8xAsiRJkqazbwA9QAdZVvI9w45fnf/sAb5Zh/dfkW/vTil9uvhARPw9WabyxWTZya8EvlKHPpBS+n7+nh/LnzqQUvpWpddERDvwZbIgcS/wmpTSjcOaXR8RHyELMK8CPhkR/5pS2lnTX0CSJEkTztIWkiRJmrZSSgcZCs6+PiKaC8ciogl4ff7wy3nbevj88CBy3rc+4L8XPXVlnd5/rN4BnJTvv6dEEBmAlNKjwFvyh62UznSWJEnSFGcgWZIkSdPddfnPhcBvFj3/MmDRsDb18LcVjv0YOJLvn13HPozFm/KfW4F/rNQwpXQzsCV/+KJ6dkqSJEkTw9IWkiRJmtZSSrdFxCPAaWQL630jP3R1/vPhlNLtdXr7A8C9Ffp2OCJ2AkvJaiVPChExDzg3f7gVeHlEjPSy/fnPs+rVL0mSJE0cA8mSJEmaCb4I/N/ASyJicf7cVUXH6mVXSimN0OZQ/nN2HfsxWicxdPfiBYyufvSkCYhLkiSpdixtIUmSpJngemCALJHiDcAb8/2B/Fi9DNTx3PU0bxyvbapZLyRJkjRpGEiWJEnStJdS2gzcnD+8mqzEBcAPU0pPTEinaq+Wn+33F+1fl1KK0Ww17IckSZImCQPJkiRJmimuy3+ey1D93+tKtpw8DhXtN4/QdtEIx0fjyaL9c2p4XkmSJE1RBpIlSZI0U3wD6Cl63MPoav9OhO6i/eUjtL24ivMVSm1UzBpOKe0EHsgfPiMiTqri3JIkSZrGDCRLkiRpRkgpHQQ+Bvw03/4mf27Syvu3IX/4zIhoK9UuIpqA91RxykLJitYq2hYWIWwAPlRFe0mSJE1jBpIlSZI0Y6SU/jyl9Kx8u3ai+1Ol7+U/5wJ/MfxgRDQCnwbOquJcj+c/F0bEqhHa/h2wMd9/Q0T8TUSULa8RER0R8f6IeEEV/ZAkSdIU0zjRHZAkSZJU0ceBt5LVSP5ARJxJVqZjH7AWeDNwBvDPwOtGONcPgZfn+9+IiE8BWxkqeXFvSulJgJRSb0S8EvgR0AFcA/xORHwF+BVZaZB24BTgIuA3gBbgTeP9hSVJkjT5GEiWJEmSJrGU0oMR8Z+Az5DdUfiSfCv2D2TlJ0YKJH8eeC9wOvCM/HXF3kLRAoQppV9ExEXAl4Dzyeo0X1Ph/IeAnSP0QZIkSVOQpS0kSZKkSS6l9DngEuArZBnE/cA24DvAb6aU3sFQVnGl8+wHngX8P8A9wN6RXpdSeogs6PwKsrrJD5NlIx8lWwzwl8D1wNXAspTS90qfSZIkSVNZpJQmug+SJEmSJEmSpEnMjGRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklSRgWRJkiRJkiRJUkUGkiVJkiRJkiRJFRlIliRJkiRJkiRVZCBZkiRJkiRJklTR/wHKcCKZKnq7KwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hour = 3\n",
    "cwt, apn, group = feature_extractor.extract_cwt(\n",
    "    file='b02', fs_new=1, smooth=True, cwt_width=40, \n",
    "    diagPlot=True, xlm=[150, 180]) #[60 * (hour - 1), 60 * hour])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Determine frequency threshold "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-15T03:24:37.701248Z",
     "start_time": "2020-02-15T03:24:37.691275Z"
    }
   },
   "outputs": [],
   "source": [
    "def freq_features(file_names):\n",
    "    df = pd.DataFrame()\n",
    "    fs_new = 2.4 # optimized from hyper-parameter tuning\n",
    "    \n",
    "    for file in file_names:\n",
    "        print(file)\n",
    "        with open(f'../data/raw/{file}.pkl', 'rb') as f:\n",
    "            res = pickle.load(f)\n",
    "            hr = res['hr']\n",
    "            t_hr = res['t'] # in minute\n",
    "            apn = res['apn']\n",
    "            group = file[0].upper() \n",
    "            \n",
    "        t_hr, hr_smth = feature_extractor.smooth_hr(t_hr, hr)\n",
    "        \n",
    "        # Resample data for frequency-domain analysis\n",
    "        t_interp = np.arange(t_hr[0], t_hr[-1], 1 / fs_new / 60)\n",
    "        hr_interp = np.interp(t_interp, t_hr, hr_smth)\n",
    "        \n",
    "        # Extract features from each segment\n",
    "        for minute in range(len(apn) - 4):\n",
    "            fea_dict = {}\n",
    "            idx_1min = (t_hr > minute + 2) & (t_hr < minute + 3)\n",
    "            idx_5min = (t_hr > minute) & (t_hr < minute + 5)\n",
    "            data_1min, data_5min = hr_smth[idx_1min], hr_smth[idx_5min]\n",
    "            \n",
    "            hr_interp_1min = hr_interp[(t_interp > minute + 2) & (t_interp < minute + 3)]\n",
    "            hr_interp_5min = hr_interp[(t_interp > minute) & (t_interp < minute + 5)]\n",
    "            \n",
    "            # Discard segment if less than 30 heart beats detected\n",
    "            if len(data_1min) < 30: \n",
    "                continue\n",
    "                \n",
    "            # Frequency-domain features\n",
    "            freq, psd = signal.periodogram(hr_interp_5min, fs=fs_new)\n",
    "            psd[freq > 0.1] = 0\n",
    "            \n",
    "            # Label information\n",
    "            fea_dict.update({\n",
    "                'apn': apn[minute + 2],\n",
    "                'group': group,\n",
    "                'file': file,\n",
    "                'psd': psd,\n",
    "                'freq': freq\n",
    "            })\n",
    "            df = df.append(fea_dict, ignore_index=True)\n",
    "                    \n",
    "    df['apn'] = df['apn'].astype(int)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-03T21:04:55.747210Z",
     "start_time": "2020-02-03T21:02:39.207452Z"
    },
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "c02\n",
      "b03\n",
      "a08\n",
      "a19\n",
      "a09\n",
      "a18\n",
      "a12\n",
      "a28\n",
      "c13\n",
      "a27\n",
      "b09\n",
      "c11\n",
      "a26\n",
      "c16\n",
      "c03\n",
      "b02\n",
      "a32\n",
      "c14\n",
      "a13\n",
      "a30\n",
      "a16\n",
      "a17\n",
      "a35\n",
      "a34\n",
      "a06\n",
      "a03\n",
      "a25\n",
      "a15\n",
      "a33\n",
      "b10\n",
      "c09\n",
      "a31\n",
      "c19\n",
      "c06\n",
      "a05\n",
      "b07\n",
      "a29\n",
      "a11\n",
      "c10\n",
      "a14\n",
      "a38\n",
      "c18\n",
      "a40\n",
      "a23\n",
      "a02\n",
      "a37\n",
      "c12\n",
      "a36\n",
      "b04\n",
      "b06\n",
      "c15\n",
      "b08\n",
      "a21\n"
     ]
    }
   ],
   "source": [
    "train_df = pd.read_csv('../resources/File_train.csv')\n",
    "df = freq_features(train_df['file'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-03T20:40:40.401892Z",
     "start_time": "2020-02-03T20:30:29.372674Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Thres=0.005: 0.774 for training, 0.774 for validation\n",
      "Thres=0.0075: 0.789 for training, 0.786 for validation\n",
      "Thres=0.009999999999999998: 0.789 for training, 0.786 for validation\n",
      "Thres=0.012499999999999999: 0.794 for training, 0.792 for validation\n",
      "Thres=0.015: 0.797 for training, 0.796 for validation\n",
      "Thres=0.017499999999999998: 0.791 for training, 0.790 for validation\n",
      "Thres=0.019999999999999997: 0.791 for training, 0.790 for validation\n",
      "Thres=0.0225: 0.781 for training, 0.778 for validation\n",
      "Thres=0.024999999999999998: 0.776 for training, 0.772 for validation\n",
      "Thres=0.027499999999999997: 0.780 for training, 0.776 for validation\n"
     ]
    }
   ],
   "source": [
    "# Optimal freq threshold for data_5min\n",
    "for thres in np.arange(0.005, 0.03, 0.0025):\n",
    "    for idx in range(len(df)):\n",
    "        psd = df.loc[idx, 'psd']\n",
    "        freq = df.loc[idx, 'freq']\n",
    "        df.loc[idx, 'peak'] = psd.max()\n",
    "        df.loc[idx, 'f_peak'] = freq[np.argmax(psd)]\n",
    "        df.loc[idx, 'area_total'] = psd.sum()\n",
    "        df.loc[idx, 'area_lf'] = psd[freq < thres].sum()\n",
    "        df.loc[idx, 'area_hf'] = psd[freq > thres].sum(),\n",
    "        df.loc[idx, 'area_ratio'] = psd[freq > thres].sum() / psd[freq < thres].sum()\n",
    "        \n",
    "    feature_col = ['peak', 'f_peak', 'area_total', 'area_lf', 'area_hf', 'area_ratio']\n",
    "    logreg = LogisticRegression(solver='lbfgs', max_iter=1e6)\n",
    "    acc_train, acc_val, _ = model_evaluation.model_evaluation_CV(logreg, df, train_df, feature_col, normalize=True, n=4)\n",
    "    print(f'Thres={thres}: {acc_train:.3f} for training, {acc_val:.3f} for validation')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Extract features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-15T03:26:05.601377Z",
     "start_time": "2020-02-15T03:26:05.584451Z"
    }
   },
   "outputs": [],
   "source": [
    "def extract_features(file):\n",
    "    fs_new = 2.4 # optimized from hyper-parameter tuning\n",
    "    thres = 0.015\n",
    "    df = pd.DataFrame()\n",
    "\n",
    "    with open(f'../data/raw/{file}.pkl', 'rb') as f:\n",
    "        res = pickle.load(f)\n",
    "        hr = res['hr']\n",
    "        t_hr = res['t'] # in minute\n",
    "        apn = res['apn']\n",
    "        group = file[0].upper() \n",
    "\n",
    "    t_hr, hr_smth = feature_extractor.smooth_hr(t_hr, hr)\n",
    "\n",
    "    # Resample data for frequency-domain analysis\n",
    "    t_interp = np.arange(t_hr[0], t_hr[-1], 1 / fs_new / 60)\n",
    "    hr_interp = np.interp(t_interp, t_hr, hr_smth)\n",
    "\n",
    "    # Extract features from each segment\n",
    "    for minute in range(len(apn) - 4):\n",
    "        fea_dict = {}\n",
    "        idx_1min = (t_hr > minute + 2) & (t_hr < minute + 3)\n",
    "        idx_5min = (t_hr > minute) & (t_hr < minute + 5)\n",
    "        data_1min, data_5min = hr_smth[idx_1min], hr_smth[idx_5min]\n",
    "\n",
    "        hr_interp_1min = hr_interp[(t_interp > minute + 2) & (t_interp < minute + 3)]\n",
    "        hr_interp_5min = hr_interp[(t_interp > minute) & (t_interp < minute + 5)]\n",
    "\n",
    "        # Discard segment if less than 30 heart beats detected\n",
    "        if len(data_1min) < 30: \n",
    "            continue\n",
    "\n",
    "        # Time-domain features for data_1min\n",
    "        md = np.median(data_1min)\n",
    "        fea_dict.update({\n",
    "            'md_1min': md,\n",
    "            'min_r_1min': data_1min.min() - md,\n",
    "            'max_r_1min': data_1min.max() - md,\n",
    "            'p25_r_1min': np.percentile(data_1min, 0.25) - md,\n",
    "            'p75_r_1min': np.percentile(data_1min, 0.75) - md,\n",
    "            'mean_r_1min': data_1min.mean() - md,\n",
    "            'std_1min': data_1min.std(),\n",
    "            'acf1_1min': pd.Series(hr_interp_1min).autocorr(12),\n",
    "            'acf2_1min': pd.Series(hr_interp_1min).autocorr(24),\n",
    "        })\n",
    "\n",
    "        # Time-domain features for data_5min\n",
    "        md = np.median(data_5min)\n",
    "        fea_dict.update({\n",
    "            'md_5min': md,\n",
    "            'min_r_5min': data_5min.min() - md,\n",
    "            'max_r_5min': data_5min.max() - md,\n",
    "            'p25_r_5min': np.percentile(data_5min, 0.25) - md,\n",
    "            'p75_r_5min': np.percentile(data_5min, 0.75) - md,\n",
    "            'mean_r_5min': data_5min.mean() - md,\n",
    "            'std_5min': data_5min.std(),\n",
    "            'acf1_5min': pd.Series(hr_interp_5min).autocorr(12),\n",
    "            'acf2_5min': pd.Series(hr_interp_5min).autocorr(24),\n",
    "        })\n",
    "\n",
    "        # Heart rate variability for data_1min\n",
    "        nn_intervals = (np.diff(t_hr[idx_1min]) * 1000 * 60).astype(int) # Unit in ms\n",
    "        time_domain_features = get_time_domain_features(nn_intervals)\n",
    "        time_domain_features = {f'{key}_1min': value for key, value in time_domain_features.items()}\n",
    "        nonlinear_features = get_csi_cvi_features(nn_intervals)\n",
    "        nonlinear_features = {f'{key}_1min': value for key, value in nonlinear_features.items()}\n",
    "        fea_dict.update(time_domain_features)\n",
    "        fea_dict.update(nonlinear_features)\n",
    "\n",
    "        # Heart rate variability for data_5min\n",
    "        nn_intervals = (np.diff(t_hr[idx_5min]) * 1000 * 60).astype(int) # Unit in ms\n",
    "        time_domain_features = get_time_domain_features(nn_intervals)\n",
    "        time_domain_features = {f'{key}_5min': value for key, value in time_domain_features.items()}\n",
    "        nonlinear_features = get_csi_cvi_features(nn_intervals)\n",
    "        nonlinear_features = {f'{key}_5min': value for key, value in nonlinear_features.items()}\n",
    "        fea_dict.update(time_domain_features)\n",
    "        fea_dict.update(nonlinear_features)\n",
    "\n",
    "        # Frequency-domain features\n",
    "        freqs, psd = signal.periodogram(hr_interp_5min, fs=fs_new)\n",
    "        psd[freqs > 0.1] = 0\n",
    "        fea_dict.update({\n",
    "            'peak': psd.max(),\n",
    "            'f_peak': freqs[np.argmax(psd)],\n",
    "            'area_total': psd.sum(),\n",
    "            'area_lf': psd[freqs < thres].sum(),\n",
    "            'area_hf': psd[freqs > thres].sum(),\n",
    "            'area_ratio': psd[freqs > thres].sum() / psd[freqs < thres].sum(),\n",
    "        })\n",
    "\n",
    "        # Label information\n",
    "        fea_dict.update({\n",
    "            'apn': apn[minute + 2],\n",
    "            'group': group,\n",
    "            'file': file,\n",
    "        })\n",
    "        df = df.append(fea_dict, ignore_index=True)\n",
    "                    \n",
    "    df['apn'] = df['apn'].astype(int)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_all = pd.read_csv('../resources/File_all.csv')\n",
    "for file in file_all['file']:\n",
    "    print(file)\n",
    "    df = extract_features(file)\n",
    "    df.dropna(inplace=True)\n",
    "    df.to_csv(f'../data/feature/{file}.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4. Feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-15T03:26:38.499418Z",
     "start_time": "2020-02-15T03:26:36.701425Z"
    }
   },
   "outputs": [],
   "source": [
    "file_train = pd.read_csv('../resources/File_train.csv')\n",
    "file_train\n",
    "\n",
    "df = pd.DataFrame()\n",
    "for file in file_train['file']:\n",
    "    df = df.append(pd.read_csv(f'../data/feature/{file}.csv'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.1 Features with high correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-06T03:56:50.959347Z",
     "start_time": "2020-02-06T03:56:50.612305Z"
    }
   },
   "outputs": [],
   "source": [
    "# Normalize features\n",
    "df_temp = df.drop(['apn', 'file', 'group'], axis=1)\n",
    "df_temp = (df_temp - df_temp.mean()) / df_temp.std()\n",
    "\n",
    "# Calculate correlations\n",
    "corr = df_temp.corr()\n",
    "corr = corr.where(np.tril(np.ones(corr.shape), k=-1).astype(np.bool))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-06T03:59:44.910115Z",
     "start_time": "2020-02-06T03:59:42.211256Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1008 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots(figsize=(16, 14))\n",
    "cmap = sns.diverging_palette(220, 10, as_cmap=True)\n",
    "sns.heatmap(corr.abs(), cmap=cmap, center=0,\n",
    "            square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n",
    "plt.savefig('../archive/Feature_correlation.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-06T03:57:00.960329Z",
     "start_time": "2020-02-06T03:57:00.932376Z"
    }
   },
   "outputs": [],
   "source": [
    "to_drop = [column for column in corr.columns if any(corr.abs()[column] > 0.98)]\n",
    "df = df.drop(to_drop, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-06T03:57:12.499567Z",
     "start_time": "2020-02-06T03:57:12.489559Z"
    }
   },
   "outputs": [],
   "source": [
    "with open('../features/feature_selection.pkl', 'wb') as f:\n",
    "    pickle.dump(list(df.drop(['apn', 'file', 'group'], axis=1).columns), f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4.2 Features with low importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-06T03:57:22.440823Z",
     "start_time": "2020-02-06T03:57:22.035878Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ExtraTreesClassifier(bootstrap=False, ccp_alpha=0.0, class_weight=None,\n",
       "                     criterion='gini', max_depth=None, max_features='auto',\n",
       "                     max_leaf_nodes=None, max_samples=None,\n",
       "                     min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                     min_samples_leaf=1, min_samples_split=2,\n",
       "                     min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=None,\n",
       "                     oob_score=False, random_state=None, verbose=0,\n",
       "                     warm_start=False)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = df.drop(['apn', 'file', 'group'], axis=1)\n",
    "X = (X - X.mean()) / X.std()\n",
    "y = df['apn']\n",
    "\n",
    "# feature extraction\n",
    "model = ExtraTreesClassifier(n_estimators=10)\n",
    "model.fit(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-06T04:00:08.692690Z",
     "start_time": "2020-02-06T04:00:07.476908Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = pd.DataFrame(data=model.feature_importances_, index=X.columns, columns=['importance'])\n",
    "ax = temp.sort_values('importance').plot.barh(figsize=(10,10))\n",
    "plt.savefig('../archive/Feature_importance.png', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Other frequency-domain features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "file = 'b02'\n",
    "fs_new = 2.4\n",
    "b, a = signal.butter(3, 0.1)\n",
    "\n",
    "with open('features/HR_' + file + '.pkl', 'rb') as f:\n",
    "    data = pickle.load(f)\n",
    "\n",
    "with open('data/processed/' + file + '.pkl', 'rb') as f:\n",
    "    apn = pickle.load(f)['apn']\n",
    "    group = util.ecg_diagnose(apn) if file[0] == 'x' else file[0].upper()   \n",
    "\n",
    "# Remove outliers    \n",
    "idx_valid = (data['hr'] < 2) & (data['hr'] > 0.5)\n",
    "hr_raw, t_raw = data['hr'][idx_valid], data['t'][idx_valid]\n",
    "\n",
    "# Smooth data\n",
    "hr_raw = signal.filtfilt(b, a, hr_raw)\n",
    "\n",
    "# Resample data for frequency-domain analysis\n",
    "t = np.arange(t_raw[0], t_raw[-1], 1 / fs_new / 60)\n",
    "hr = np.interp(t, t_raw, hr_raw)\n",
    "\n",
    "minute = 0\n",
    "idx = (t > minute) & (t < minute + 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# STFT\n",
    "f, t_stft, Zxx = signal.stft(\n",
    "    hr[idx], fs=fs_new, window='hann', \n",
    "    nperseg=24*6, noverlap=None, nfft=None, detrend=False, \n",
    "    return_onesided=True, boundary='zeros', padded=True)\n",
    "plt.pcolormesh(t_stft, f, np.abs(Zxx))\n",
    "plt.title('STFT Magnitude')\n",
    "plt.ylabel('Frequency [Hz]')\n",
    "plt.xlabel('Time [sec]')\n",
    "plt.ylim([0, 0.1])\n",
    "plt.show()\n",
    "\n",
    "# spectrogram\n",
    "f, t_sg, Sxx = signal.spectrogram(\n",
    "    hr[idx], fs=fs_new,\n",
    "    window='hann', nperseg=24*6, noverlap=None, \n",
    "    nfft=None, detrend=False, return_onesided=True, \n",
    "    scaling='density', mode='psd')\n",
    "plt.pcolormesh(t_sg, f, Sxx)\n",
    "plt.ylabel('Frequency [Hz]')\n",
    "plt.xlabel('Time [sec]')\n",
    "plt.xlim([0, 300])\n",
    "plt.ylim([0, 0.1])\n",
    "plt.show()\n",
    "\n",
    "# MFCC\n",
    "mfccs = librosa.feature.mfcc(y=hr, sr=fs_new, n_mfcc=40)\n",
    "print(mfccs.shape)\n",
    "plt.figure(figsize=(10, 4))\n",
    "librosa.display.specshow(mfccs, x_axis='time')\n",
    "# plt.xlim([0, 5])\n",
    "plt.colorbar()\n",
    "plt.title('MFCC')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.1"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": false,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  },
  "varInspector": {
   "cols": {
    "lenName": 16,
    "lenType": 16,
    "lenVar": 40
   },
   "kernels_config": {
    "python": {
     "delete_cmd_postfix": "",
     "delete_cmd_prefix": "del ",
     "library": "var_list.py",
     "varRefreshCmd": "print(var_dic_list())"
    },
    "r": {
     "delete_cmd_postfix": ") ",
     "delete_cmd_prefix": "rm(",
     "library": "var_list.r",
     "varRefreshCmd": "cat(var_dic_list()) "
    }
   },
   "types_to_exclude": [
    "module",
    "function",
    "builtin_function_or_method",
    "instance",
    "_Feature"
   ],
   "window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
